SwePub - sökning: WFRF:(Svensson Lennart 1976)

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1.	Crouse, David F., et al. (författare) The Set MHT 2011 Ingår i: 14th International Conference on Information Fusion, Fusion 2011; Chicago, IL; 5 July 2011 through 8 July 2011. - 9781457702679 Konferensbidrag (refereegranskat)abstract Abstract—We introduce the Set MHT, a tracking algorithmthat maintains multiple hypotheses and produces “smooth”estimates without the track coalescence often associated withMinimum Mean Squared Error (MMSE) estimation or thejitter associated with Maximum Likelihood (ML) estimation.It does this by utilizing Minimum Mean Optimal SubpatternAssignment (MMOSPA) estimation techniques coupled with atheoretically-grounded approach for probabilistically determiningthe identities of the state estimates. Unlike traditional MHTalgorithms, the Set MHT does not “forget” uncertainty in targetidentities, i.e. display an unjustifiably high confidence level inthe target identities, as a result of pruning out competinghypotheses. Rather, it uses merging techniques while avoiding theshortcomings of traditional Gaussian mixture reduction trackers.
2.	Fejgin, Kim, 1978, et al. (författare) Nitric oxide and GABAB-sensitive mechanisms in the prefrontal cortex are important for the disruptive effects of phencyclidine on prepulse inhibition 2008 Ingår i: Presented at Cognitive Dysfunctions in Disease: Mechanisms and Therapies. April 2008, Stockholm, Sweden. Konferensbidrag (refereegranskat)
3.	Fejgin, Kim, 1978, et al. (författare) Nitric oxide signaling in the medial prefrontal cortex is involved in the biochemical and behavioral effects of phencyclidine. 2008 Ingår i: Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology. - : Springer Science and Business Media LLC. - 0893-133X. ; 33:8, s. 1874-83 Tidskriftsartikel (refereegranskat)abstract The prefrontal cortex (PFC) is believed to play an important role in the cognitive impairments observed in schizophrenia and has also been shown to be involved in the modulation of prepulse inhibition (PPI), a measure of preattentive information processing that is impaired in schizophrenic individuals. Phencyclidine (PCP), a noncompetitive inhibitor of the NMDA receptor, exerts psychotomimetic effects in humans, disrupts PPI, and causes hypofrontality in rodents and monkeys. We have previously demonstrated that interfering with the production of nitric oxide (NO) can prevent a wide range of PCP-induced behavioral deficits, including PPI disruption. In the present study, the role of NO signaling for the behavioral and biochemical effects of PCP was further investigated. Dialysate from the medial PFC of mice receiving systemic treatment with PCP and/or the NO synthase inhibitor, N(G)-nitro-L-arginine methyl ester (L-NAME, 40 mg/kg), was analyzed for cGMP content. Furthermore, a specific inhibitor of NO-sensitive soluble guanylyl cyclase (sGC), 1H-(1,2,4)oxadiazolo(4,3-a)quinoxalin-1-one (ODQ, 0.01-1 mM), was administered into the medial PFC of mice in combination with systemic injections of PCP, followed by PPI and locomotor activity testing. PCP (5 mg/kg) caused an increase in prefrontal cGMP that could be attenuated by pretreatment with the NO synthase inhibitor, L-NAME. Moreover, bilateral microinjection of the sGC inhibitor, ODQ, into the medial PFC of mice attenuated the disruption of PPI, but not the hyperlocomotion, caused by PCP. The present study shows that NO/sGC/cGMP signaling pathway in the medial PFC is involved in specific behavioral effects of PCP that may have relevance for the disabling cognitive dysfunction found in patients with schizophrenia.
4.	Fejgin, Kim, 1978, et al. (författare) The atypical antipsychotic, aripiprazole, blocks phencyclidine-induced disruption of prepulse inhibition in mice. 2007 Ingår i: Psychopharmacology. - : Springer Science and Business Media LLC. - 0033-3158 .- 1432-2072. ; 191:2, s. 377-85 Tidskriftsartikel (refereegranskat)abstract RATIONALE: The psychotomimetic drug, phencyclidine, induces schizophrenia-like behavioural changes in both humans and animals. Phencyclidine-induced disruption of sensory motor gating mechanisms, as assessed by prepulse inhibition of the acoustic startle, is widely used in research animals as a screening model for antipsychotic properties in general and may predict effects on negative and cognitive deficits in particular. Dopamine (DA) stabilizers comprise a new generation of antipsychotics characterized by a partial DA receptor agonist or antagonist action and have been suggested to have a more favourable clinical profile. OBJECTIVE: The aim of the present study was to investigate the ability of first, second and third generation antipsychotics to interfere with the disruptive effect of phencyclidine on prepulse inhibition in mice. RESULTS: Aripiprazole blocked the phencyclidine-induced disruption of prepulse inhibition. The atypical antipsychotic clozapine was less effective, whereas olanzapine, and the typical antipsychotic haloperidol, failed to alter the effects of phencyclidine on prepulse inhibition. CONCLUSIONS: The somewhat superior efficacy of clozapine compared to haloperidol may be explained by its lower affinity and faster dissociation rate for DA D2 receptors possibly combined with an interaction with other receptor systems. Aripiprazole was found to be more effective than clozapine or olanzapine, which may be explained by a partial agonist activity of aripiprazole at DA D2 receptors. In conclusion, the present findings suggest that partial DA agonism leading to DA stabilizing properties may have favourable effects on sensorimotor gating and thus tentatively on cognitive dysfunctions in schizophrenia.
5.	Ge, Yu, 1995, et al. (författare) 5G SLAM Using the Clustering and Assignment Approach with Diffuse Multipath 2020 Ingår i: Sensors. - : MDPI AG. - 1424-8220. ; 20:16, s. 1-31 Tidskriftsartikel (refereegranskat)abstract 5G communication systems operating above 24 GHz have promising properties for user localization and environment mapping. Existing studies have either relied on simplified abstract models of the signal propagation and the measurements, or are based on direct positioning approaches, which directly map the received waveform to a position. In this study, we consider an intermediate approach, which consists of four phases-downlink data transmission, multi-dimensional channel estimation, channel parameter clustering, and simultaneous localization and mapping (SLAM) based on a novel likelihood function. This approach can decompose the problem into simpler steps, thus leading to lower complexity. At the same time, by considering an end-to-end processing chain, we are accounting for a wide variety of practical impairments. Simulation results demonstrate the efficacy of the proposed approach.
6.	Ge, Yu, 1995, et al. (författare) 5G SLAM with Low-complexity Channel Estimation 2021 Ingår i: 15th European Conference on Antennas and Propagation, EuCAP 2021. Konferensbidrag (refereegranskat)abstract 5G millimeter-wave signals are beneficial for simultaneous localization and mapping (SLAM), due to their inherent geometric connection to the propagation environment. Channel estimators can exploit received signals to estimate multipath components in terms of delays and angles, which can be used in localization and mapping. Thus, a good channel estimator is essential for 5G SLAM. This paper presents a novel low-complexity multidimensional ESPRIT-based channel estimator and applies it to a 5G SLAM framework. Simulation results demonstrate that the proposed channel estimator can accurately estimate channel information with low computational cost, with limited impact on mapping performance, compared to a tensor-ESPRIT benchmark.
7.	Ge, Yu, 1995, et al. (författare) A Computationally Efficient EK-PMBM Filter for Bistatic mmWave Radio SLAM 2022 Ingår i: IEEE Journal on Selected Areas in Communications. - 0733-8716 .- 1558-0008. ; 40:7, s. 2179-2192 Tidskriftsartikel (refereegranskat)abstract Millimeter wave (mmWave) signals are useful for simultaneous localization and mapping (SLAM), due to their inherent geometric connection to the propagation environment and the propagation channel. To solve the SLAM problem, existing approaches rely on sigma-point or particle-based approximations, leading to high computational complexity, precluding real-time execution. We propose a novel low-complexity SLAM filter, based on the Poisson multi-Bernoulli mixture (PMBM) filter. It utilizes the extended Kalman (EK) first-order Taylor series based Gaussian approximation of the filtering distribution, and applies the track-oriented marginal multi-Bernoulli/Poisson (TOMB/P) algorithm to approximate the resulting PMBM as a Poisson multi-Bernoulli (PMB). The filter can account for different landmark types in radio SLAM and multiple data association hypotheses. Hence, it has an adjustable complexity/performance trade-off. Simulation results show that the developed SLAM filter can greatly reduce the computational cost, while it keeps the good performance of mapping and user state estimation.
8.	Ge, Yu, 1995, et al. (författare) Doppler Exploitation in Bistatic mmWave Radio SLAM 2022 Ingår i: GLOBECOM - IEEE Global Telecommunications Conference. ; , s. 6463-6468 Konferensbidrag (refereegranskat)abstract Networks in 5G and beyond utilize millimeter wave (mmWave) radio signals, large bandwidths, and large antenna arrays, which bring opportunities in jointly localizing the user equipment and mapping the propagation environment, termed as simultaneous localization and mapping (SLAM). Existing approaches mainly rely on delays and angles, and ignore the Doppler, although it contains geometric information. In this paper, we study the benefits of exploiting Doppler in SLAM through deriving the posterior Cram´er-Rao bounds (PCRBs) and formulating the extended Kalman-Poisson multi-Bernoulli sequential filtering solution with Doppler as one of the involved measurements. Both theoretical PCRB analysis and simulation results demonstrate the efficacy of utilizing Doppler.
9.	Ge, Yu, 1995, et al. (författare) Experimental Validation of Single Base Station 5G mm Wave Positioning: Initial Findings 2022 Ingår i: 2022 25th International Conference on Information Fusion, FUSION 2022. - Piscataway : IEEE. Konferensbidrag (refereegranskat)abstract 5G cellular networks can utilize millimeter wave signals, and support large bandwidths and large antenna arrays, which provide more geometric-based signals and higher delay and angle resolutions. These merits bring new opportunities in positioning the user with limited infrastructure through the use of combined angle and delay information. However, there are many practical challenges to overcome, in order to have a functioning single base station 5G mmWave positioning system. In this paper, we describe a deployed single base station mmWave positioning system, and provide an example of the measurement data. Furthermore, we perform measurement validation on a limited measurement data set by performing base station localization. Additional evaluations performed on simulation model data provide guidelines on the required size of the data set and receiver antenna configuration, which will be implemented in upcoming measurements.
10.	Ge, Yu, 1995, et al. (författare) Experimental Validation of Single BS 5G mmWave Positioning and Mapping for Intelligent Transport 2024 Ingår i: IEEE Transactions on Vehicular Technology. - 0018-9545 .- 1939-9359. ; In Press Tidskriftsartikel (refereegranskat)abstract Positioning with 5G signals generally requires connection to several base stations (BSs), which makes positioning more demanding in terms of infrastructure than communications. To address this issue, there have been several theoretical studies on single BS positioning, leveraging high-resolution angle and delay estimation and multipath exploitation possibilities at mmWave frequencies. This paper presents the first realistic experimental validation of such studies, involving a commercial 5G mmWave BS with a customized beam sweep procedure and a user equipment (UE) development kit mounted on a test vehicle. We present the relevant signal models, and signal processing methods, and validate these based on data collected in an outdoor science park environment. Our results indicate that positioning is possible, but the performance is limited by the knowledge of the position and orientation of the infrastructure and the multipath visibility and diversity
11.	Ge, Yu, 1995, et al. (författare) Exploiting Diffuse Multipath in 5G SLAM 2020 Ingår i: 2020 IEEE Global Communications Conference, GLOBECOM 2020 - Proceedings. Konferensbidrag (refereegranskat)abstract 5G millimeter wave (mmWave) signals can be used to jointly localize the receiver and map the propagation environment in vehicular networks, which is a typical simultaneous localization and mapping (SLAM) problem. Mapping the environment is challenging, due to measurements comprising both specular and diffuse multipath components, where diffuse multipath is usually considered as a perturbation. We here propose a novel method to utilize all available multipath signals from each landmark for mapping and incorporate this into a Poisson multi-Bernoulli mixture for the 5G SLAM problem. Simulation results demonstrate the efficacy of the proposed scheme.
12.	Ge, Yu, 1995, et al. (författare) Integrated Monostatic and Bistatic mmWave Sensing 2023 Ingår i: Proceedings - IEEE Global Communications Conference, GLOBECOM. - 2334-0983 .- 2576-6813. ; , s. 3897-3903 Konferensbidrag (refereegranskat)abstract Millimeter-wave (mmWave) signals provide attractive opportunities for sensing due to their inherent geometrical connections to physical propagation channels. Two common modalities used in mmWave sensing are monostatic and bistatic sensing, which are usually considered separately. By integrating these two modalities, information can be shared between them, leading to improved sensing performance. In this paper, we investigate the integration of monostatic and bistatic sensing in a 5G mmWave scenario, implement the extended Kalman-Poisson multi-Bernoulli sequential filters to solve the sensing problems, and propose a method to periodically fuse user states and maps from two sensing modalities.
13.	Ge, Yu, 1995, et al. (författare) Iterated Posterior Linearization PMB Filter for 5G SLAM 2022 Ingår i: IEEE International Conference on Communications. - 1550-3607. ; 2022-May, s. 877-882 Konferensbidrag (refereegranskat)abstract 5G millimeter wave (mmWave) signals have inherent geometric connections to the propagation channel and the propagation environment. Thus, they can be used to jointly localize the receiver and map the propagation environment, which is termed as simultaneous localization and mapping (SLAM). One of the most important tasks in the 5G SLAM is to deal with the nonlinearity of the measurement model. To solve this problem, existing 5G SLAM approaches rely on sigma-point or extended Kalman filters, linearizing the measurement function with respect to the prior probability density function (PDF). In this paper, we study the linearization of the measurement function with respect to the posterior PDF, and implement the iterated posterior linearization filter into the Poisson multi-Bernoulli SLAM filter. Simulation results demonstrate the accuracy and precision improvements of the resulting SLAM filter.
14.	Ge, Yu, 1995, et al. (författare) MmWave Mapping and SLAM for 5G and Beyond 2023 Ingår i: Integrated Sensing and Communications. - 9789819925018 ; , s. 445-475 Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract Device localization and radar-like mapping are at the heart of integrated sensing and communication, enabling not only new services and applications, but also improving communication quality with reduced overheads. These forms of sensing are however susceptible to data association problems, due to the unknown relation between measurements and detected objects or targets. In this chapter, we provide an overview of the fundamental tools used to solve mapping, tracking, and simultaneous localization and mapping (SLAM) problems. We distinguish the different types of sensing problems and then focus on mapping and SLAM as running examples. Starting from the applicable models and definitions, we describe the different algorithmic approaches, with a particular focus on how to deal with data association problems. In particular, methods based on random finite set theory and Bayesian graphical models are introduced in detail. A numerical study with synthetic and experimental data is then used to compare these approaches in a variety of scenarios.
15.	Guerriero, Marco, et al. (författare) Set JPDA Algorithm for Tracking Sonar Crossing Targets 2009 Ingår i: Proceedings of NATO Workshop on Data Fusion and Anomaly Detection for Maritime Situational Awareness. Konferensbidrag (refereegranskat)
16.	Guerriero, Marco, et al. (författare) Shooting two birds with two bullets: how to find Minimum Mean OSPA estimates 2010 Ingår i: Proceedings of the 13th International Conference on Information Fusion. Konferensbidrag (refereegranskat)abstract Most area-defense formulations followfrom the assumption that threats must first be identifiedand then neutralized. This is reasonable, but inherentto it is a process of labeling: threat A must be identifiedand then threat B, and then action must be taken.This manuscript begins from the assumption that suchlabeling (A & B) is irrelevant. The problem naturallydevolves to one of Random Finite Set (RFS) estimation:we show that by eschewing any concern of targetlabel we relax the estimation procedure, and it is perhapsnot surprising that by such a removal of constraint (oflabeling) performance (in terms of localization) is enhanced.A suitable measure for the estimation of unlabeledobjects is the Mean OSPA (MOSPA). We derive ageneral algorithm which provided the optimal estimatorwhich minimize the MOSPA. We call such an estimatora Minimum MOSPA (MMOSPA) estimator.
17.	Gunnarsson, Joakim, 1976, et al. (författare) Coordinate transformations and implementation details for a new vehicle motion model 2007 Rapport (övrigt vetenskapligt/konstnärligt)
18.	Gunnarsson, Joakim, 1976, et al. (författare) Joint driver intention classification and tracking of vehicles 2006 Ingår i: Proc. Nonlinear Statistical Signal Processing Workshop, NSSPW. Konferensbidrag (refereegranskat)abstract In this paper we present and validate a new modelling frameworkfor joint driver intention classification and tracking ofvehicles; a framework derived for automotive active safetysystems. Such systems require reliable predictions of the trafficsituation to act in time when a dangerous situation occur.Our proposal has two main benefits. First, it incorporatesthe intention of the driver into the vehicle motion model andthereby improves the prediction capability. The result is amultiple motion model where each model corresponds to aspecific driver intent. Second, the connection between differentdriver plans and corresponding motion model enables aformal classification of the most likely driver intention. Tovalidate our concept, we apply the motion model on real datausing a particle filter implementation. Initial studies indicatepromising performance.
19.	Gunnarsson, Joakim, 1976, et al. (författare) Tracking vehicles using radar detections 2007 Ingår i: 2007 IEEE Intelligent Vehicles Symposium, IV 2007; Istanbul; Turkey; 13 June 2007 through 15 June 2007. - : IEEE. - 1424410681 ; , s. 296-302 Konferensbidrag (refereegranskat)abstract This paper is concerned with the problem of tracking vehicles using radar detections. In particular, we deal with problems where multiple detections are received from each target. According to recent studies, automotive radar sensors often receive detections from a discrete set of reflection centers. From these results, we develop a family of sensor models suitable for tracking. A significant difficulty in performing tracking using models from this family is that it involves solving a data association problem with a large number of association hypotheses. To reduce the complexity of this problem, we propose a framework where similar hypotheses are joined into groups. Following this approximation, basic data association algorithms can be implemented and initial studies using both simulated data and real measurements show a promising performance.
20.	Hashemzadeh, Parham, 1976, et al. (författare) Tracking Conductivity Variations in The Absence of Accurate State Evolution Models in Electrical Impedance Tomography 2010 Ingår i: Proceedings of the 4th International Conference on Bioinformatics and Biomedical Engineering. Konferensbidrag (refereegranskat)abstract We present results on both linear and non-linear approaches in tracking conductivity variations in electrical impedance tomography. Throughout this study, we use both synthetic and measured data. The true system dynamics is considered as unknown and modelled as a random walk. In the linear reconstructions, the time evolution model is augmented with a Gaussian smoothness prior and results are shown using two different models for the covariance matrix of the process noise. Furthermore, we compare the reconstructions of the one step Gauss-Newton method to the Kalman filter on measured data from an adult human subject. In the non-linear study, we compare the performance of the extended Kalman filter against the particle filter on a simple test case. It is observed that the particle filter shows superior performance in tracking nonlinear/non-Gaussian conductivity variations.
21.	Hess, Georg, 1996, et al. (författare) Masked Autoencoder for Self-Supervised Pre-Training on Lidar Point Clouds 2023 Ingår i: Proceedings - 2023 IEEE/CVF Winter Conference on Applications of Computer Vision Workshops, WACVW 2023. ; , s. 350-359 Konferensbidrag (refereegranskat)abstract Masked autoencoding has become a successful pretraining paradigm for Transformer models for text, images, and, recently, point clouds. Raw automotive datasets are suitable candidates for self-supervised pre-training as they generally are cheap to collect compared to annotations for tasks like 3D object detection (OD). However, the development of masked autoencoders for point clouds has focused solely on synthetic and indoor data. Consequently, existing methods have tailored their representations and models toward small and dense point clouds with homogeneous point densities. In this work, we study masked autoencoding for point clouds in an automotive setting, which are sparse and for which the point density can vary drastically among objects in the same scene. To this end, we propose Voxel-MAE, a simple masked autoencoding pre-training scheme designed for voxel representations. We pre-train the backbone of a Transformer-based 3D object detector to reconstruct masked voxels and to distinguish between empty and non-empty voxels. Our method improves the 3D OD performance by 1.75 mAP points and 1.05 NDS on the challenging nuScenes dataset. Further, we show that by pre-training with Voxel-MAE, we require only 40 of the annotated data to outperform a randomly initialized equivalent. Code is available at https://github.com/georghess/voxel-mae.
22.	Kianfar, Roozbeh, 1984, et al. (författare) Design and Experimental Validation of a Cooperative Driving System in the Grand Cooperative Driving Challenge 2012 Ingår i: IEEE Transactions on Intelligent Transportation Systems. - 1524-9050 .- 1558-0016. ; 13:3, s. 994-1007 Tidskriftsartikel (refereegranskat)abstract In this paper, we present the Cooperative Adaptive Cruise Control (CACC) architecture, which was proposed and implemented by the team from Chalmers University of Technology, Göteborg, Sweden, that joined the Grand Cooperative Driving Challenge (GCDC) in 2011. The proposed CACC architecture consists of the following three main components, which are described in detail: 1) communication; 2) sensor fusion; and 3) control. Both simulation and experimental results are provided, demonstrating that the proposed CACC system can drive within a vehicle platoon while minimizing the inter-vehicle spacing within the allowed range of safety distances, tracking a desired speed profile, and attenuating acceleration shockwaves.
23.	Kim, Hyowon, 1987, et al. (författare) PMBM-Based SLAM Filters in 5G mmWave Vehicular Networks 2022 Ingår i: IEEE Transactions on Vehicular Technology. - 0018-9545 .- 1939-9359. ; 71:8, s. 8646-8661 Tidskriftsartikel (refereegranskat)abstract Radio-based vehicular simultaneous localization and mapping (SLAM) aims to localize vehicles while mapping the landmarks in the environment. We propose a sequence of three Poisson multi-Bernoulli mixture (PMBM) based SLAM filters, which handle the entire SLAM problem in a theoretically optimal manner. The complexity of the three proposed SLAM filters is progressively reduced while sustaining high accuracy by deriving SLAM density approximation with the marginalization of nuisance parameters (either vehicle state or data association). Firstly, the PMBM SLAM filter serves as the foundation, for which we provide the first complete description based on a Rao-Blackwellized particle filter. Secondly, the Poisson multi-Bernoulli (PMB) SLAM filter is based on the standard reduction from PMBM to PMB, but involves a novel interpretation based on auxiliary variables and a relation to Bethe free energy. Finally, using the same auxiliary variable argument, we derive a marginalized PMB SLAM filter, which avoids particles and is instead implemented with a low-complexity cubature Kalman filter. We evaluate the three proposed SLAM filters in comparison with the probability hypothesis density (PHD) SLAM filter in 5G mmWave vehicular networks and show the computation-performance trade-off between them.
24.	Kim, Hyowon, et al. (författare) Set-Type Belief Propagation with Applications to Poisson Multi-Bernoulli SLAM 2024 Ingår i: IEEE Transactions on Signal Processing. - 1941-0476 .- 1053-587X. ; 72, s. 1989-2005 Tidskriftsartikel (refereegranskat)abstract Belief propagation (BP) is a useful probabilistic inference algorithm for efficiently computing approximate marginal probability densities of random variables. However, in its standard form, BP is only applicable to the vector-type random variables with a fixed and known number of vector elements, while certain applications rely on random finite sets (RFSs) with an unknown number of vector elements. In this paper, we develop BP rules for factor graphs defined on sequences of RFSs where each RFS has an unknown number of elements, with the intention of deriving novel inference methods for RFSs. Furthermore, we show that vector-type BP is a special case of set-type BP, where each RFS follows the Bernoulli process. To demonstrate the validity of developed set-type BP, we apply it to the Poisson multi-Bernoulli (PMB) filter for simultaneous localization and mapping (SLAM), which naturally leads to a set-type BP PMB-SLAM method, which is analogous to a vector type SLAM method, subject to minor modifications.
25.	Klamer, Daniel, 1976, et al. (författare) Antagonism of the nitric oxide synthase inhibitor, L-NAME, of the effects of phencyclidine on latent inhibition in taste aversion conditioning 2005 Ingår i: Behav Brain Res. ; 161:1, s. 60-8 Tidskriftsartikel (refereegranskat)abstract Latent inhibition (LI) is a behavioural procedure used to evaluate the potential propsychotic and antipsychotic properties of psychoactive drugs. In the present study, a conditioned taste aversion (CTA) procedure was used to investigate the effects of the nitric oxide (NO) synthase inhibitor, N(G)-nitro-L-arginine methyl ester (L-NAME), and the psychotomimetic drugs, phencyclidine (PCP) and d-amphetamine (d-AMP) on LI. PCP (2 mg/kg) and d-AMP (0.5 mg/kg) were both found to enhance LI in this procedure. The effect of d-AMP on LI was less pronounced and this drug also caused a weak disruption of taste aversion conditioning. Pretreatment with L-NAME (10 mg/kg) blocked the LI enhancing effect of PCP on LI but not that of d-AMP. L-NAME by itself caused an attenuation of LI. L-NAME has been shown to block also other behavioural and biochemical effects of PCP in previous studies and these results and the present findings suggest that at least some of the effects PCP are dependent on NO and possibly also that some NOS inhibitors may exert antipsychotic properties.
26.	Klamer, Daniel, 1976, et al. (författare) Cognitive dysfunctions in schizophrenia: focus on the nitric oxide pathway in rodent models 2008 Ingår i: Presented at Cognitive Dysfunctions in Disease: Mechanisms and Therapies. Stockholm, Sweden. April 2008. Konferensbidrag (refereegranskat)
27.	Klamer, Daniel, 1976, et al. (författare) Systemic adminstration of Phencyclidine increases Nitric oxide levels in the rat medial prefrontal cortex 2008 Ingår i: Presented at EWCBR. March, 2008, Les Arcs, France. Konferensbidrag (refereegranskat)
28.	Krishnan, Rajet, 1982, et al. (författare) Variational Bayesian Framework for Receiver Design in the Presence of Phase Noise in MIMO Systems 2012 Ingår i: IEEE Wireless Communications and Networking Conference, WCNC. - 1525-3511. - 9781467304375 ; , s. 347-352 Konferensbidrag (refereegranskat)abstract In this work, the problem of receiver design for phasenoise estimation and data detection in the presence of oscillator phase noise in a point-to-point multiple-input multiple-output (MIMO) system is addressed. First, we discuss some interesting and challenging aspects in receiver design for MIMO systems in thepresence of Wiener phase noise. Then, using the variational Bayesian (VB) framework, a joint iterative phase noise estimator and symbol detector are developed based on inverse Gibbs or variational free energy maximization. Further, the symbol error probability (SEP) of the newly proposed iterative scheme is compared with the optimal ML detector with perfect phase information for 16-PSK and 16-QAM modulation schemes.
29.	Moberg, John, et al. (författare) Bayesian Linear Regression on Deep Representations 2019 Ingår i: Advances in Neural Information Processing Systems 32. Konferensbidrag (refereegranskat)abstract A simple approach to obtaining uncertainty-aware neural networks for regression is to do Bayesian linear regression (BLR) on the representation from the last hidden layer. Recent work [Riquelme et al., 2018, Azizzadenesheli et al., 2018] indicates that the method is promising, though it has been limited to homoscedastic noise. In this paper, we propose a novel variation that enables the method to flexibly model heteroscedastic noise. The method is benchmarked against two prominent alternative methods on a set of standard datasets, and finally evaluated as an uncertainty-aware model in model-based reinforcement learning. Our experiments indicate that the method is competitive with standard ensembling, and ensembles of BLR outperforms the methods we compared to.
30.	Pinto, Juliano, 1990, et al. (författare) An Uncertainty-Aware Performance Measure for Multi-Object Tracking 2021 Ingår i: IEEE Signal Processing Letters. - 1070-9908 .- 1558-2361. ; 28, s. 1689-1693 Tidskriftsartikel (refereegranskat)abstract Evaluating the performance of multi-object tracking (MOT) methods is not straightforward, and existing performance measures fail to consider all the available uncertainty information in the MOT context. This can lead practitioners to select models which produce uncertainty estimates of lower quality, negatively impacting any downstream systems that rely on them. Additionally, most MOT performance measures have hyperparameters, which makes comparisons of different trackers less straightforward. We propose the use of the negative log-likelihood (NLL) of the multi-object posterior given the set of ground-truth objects as a performance measure. This measure takes into account all available uncertainty information in a sound mathematical manner without hyperparameters. We provide efficient algorithms for approximating the computation of the NLL for several common MOT algorithms, show that in some cases it decomposes and approximates the widely-used GOSPA metric, and provide several illustrative examples highlighting the advantages of the NLL in comparison to other MOT performance measures.
31.	Pinto, Juliano, 1990, et al. (författare) Deep Learning for Model-Based Multi-Object Tracking 2023 Ingår i: IEEE Transactions on Aerospace and Electronic Systems. - : IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC. - 1557-9603 .- 0018-9251. ; 59:6, s. 7363-7379 Tidskriftsartikel (refereegranskat)abstract Multi-object tracking (MOT) is the problem of tracking the state of an unknown and time-varying number of objects using noisy measurements, with important applications such as autonomous driving, tracking animal behavior, defense systems, and others. The MOT task can be divided into two settings, model-based or model-free, depending on whether accurate and tractable models of the environment are available. Model-based MOT has Bayes-optimal closed-form solutions which can achieve state-of-the-art (SOTA) performance. However, these methods require approximations in challenging scenarios to remain tractable, which impairs their performance. Deep learning (DL) methods offer a promising alternative, but existing DL models are almost exclusively designed for a model-free setting and are not easily translated to the model-based setting. This paper proposes a DL-based tracker specifically tailored to the model-based MOT setting and provides a thorough comparison to SOTA alternatives. We show that our DL-based tracker is able to match performance to the benchmarks in simple tracking tasks while outperforming the alternatives as the tasks become more challenging. These findings provide strong evidence of the applicability of DL also to the model-based setting, which we hope will foster further research in this direction.
32.	Pinto, Juliano, 1990, et al. (författare) Next Generation Multitarget Trackers: Random Finite Set Methods vs Transformer-based Deep Learning 2021 Ingår i: Proceedings of 2021 IEEE 24th International Conference on Information Fusion, FUSION 2021. ; , s. 1059-1066 Konferensbidrag (refereegranskat)abstract Multitarget Tracking (MTT) is the problem of tracking the states of an unknown number of objects using noisy measurements, with important applications to autonomous driving, surveillance, robotics, and others. In the model-based Bayesian setting, there are conjugate priors that enable us to express the multi-object posterior in closed form, which could theoretically provide Bayes-optimal estimates. However, the posterior involves a super-exponential growth of the number of hypotheses over time, forcing state-of-the-art methods to resort to approximations for remaining tractable, which can impact their performance in complex scenarios. Model-free methods based on deep-learning provide an attractive alternative, as they can, in principle, learn the optimal filter from data, but to the best of our knowledge were never compared to current state-of-the-art Bayesian filters, specially not in contexts where accurate models are available. In this paper, we propose a high-performing deeplearning method for MTT based on the Transformer architecture and compare it to two state-of-the-art Bayesian filters, in a setting where we assume the correct model is provided. Although this gives an edge to the model-based filters, it also allows us to generate unlimited training data. We show that the proposed model outperforms state-of-the-art Bayesian filters in complex scenarios, while matching their performance in simpler cases, which validates the applicability of deep-learning also in the model-based regime. The code for all our implementations is made available at https://github.com/JulianoLagana/MT3.
33.	Pålsson, Erik, 1975, et al. (författare) Increased cortical nitric oxide release after phencyclidine administration. 2009 Ingår i: Synapse (New York, N.Y.). - : Wiley. - 1098-2396 .- 0887-4476. ; 63:12, s. 1083-1088 Tidskriftsartikel (refereegranskat)abstract Phencyclidine exerts psychotomimetic effects in humans and is used as a pharmacological animal model for schizophrenia. We, and others, have demonstrated that phencyclidine induces cognitive deficits in rats that are associated with schizophrenia. These cognitive deficits can be normalized by inhibition of nitric oxide synthase. The development of selective microelectrochemical nitric oxide sensors may provide direct evidence for the involvement of nitric oxide in these effects. The aim of the present study was to use LIVE (long term in vivo electrochemistry) to investigate the effect of phencyclidine, alone or in combination with the nitric oxide synthase inhibitor L-NAME, on nitric oxide levels in the medial prefrontal cortex of freely moving rats. Phencyclidine (2 mg kg(-1)) produced an increase in cortical nitric oxide levels and this increase was ameliorated by L-NAME (10 mg kg(-1)). Tentatively, the results from the present study provide a biochemical rationale for the involvement of nitric oxide in the phencyclidine model of schizophrenia. Synapse 63:1083-1088, 2009. (c) 2009 Wiley-Liss, Inc.
34.	Pålsson, Erik, 1975, et al. (författare) The amino acid L-lysine blocks the disruptive effect of phencyclidine on prepulse inhibition in mice. 2007 Ingår i: Psychopharmacology. - : Springer Science and Business Media LLC. - 0033-3158 .- 1432-2072. ; 192:1, s. 9-15 Tidskriftsartikel (refereegranskat)abstract RATIONALE: The cognitive and attentional deficits observed in schizophrenic patients are now considered central to the pathophysiology of the disorder. These deficits include an inability to filter sensory input as measured by, e.g., prepulse inhibition (PPI) reflex. Administration of phencyclidine (PCP), a drug that can induce a schizophrenia-like psychosis in humans, disrupts PPI in experimental animals. In rodents, this PCP-induced deficit can be blocked by pretreatment with nitric oxide (NO) synthase inhibitors. This suggests that some of the behavioral effects of PCP are mediated via NO. The substrate for in vivo NO production is L-arginine, and active transport of L-arginine via the cationic amino acid transporter may serve as a regulatory mechanism in NO production. OBJECTIVES: The aim of the present study was to study the effects of L-arginine transport inhibition, using acute and repeated L-lysine treatment, on PCP-induced disruption of PPI in mice. RESULTS: Subchronic, and to some extent acute, pretreatment with L-lysine blocked a PCP-induced deficit in PPI without affecting basal PPI. CONCLUSIONS: L-lysine has been shown to block L-arginine transport in vitro, most likely via a competitive blockade and down regulation of cationic amino acid transporters. However, the importance of L-arginine transport as a regulatory mechanism in NO production in vivo is still not clear. The present results lend further support to the notion that some of the effects of PCP in the central nervous system are mediated via NO and that L-arginine transport may play a role in the regulation of NO production in the brain.
35.	Pålsson, Erik, 1975, et al. (författare) The effects of phencyclidine on latent inhibition in taste aversion conditioning: differential effects of preexposure and conditioning 2005 Ingår i: Behav Brain Res. ; 157:1, s. 139-46 Tidskriftsartikel (refereegranskat)abstract Latent inhibition (LI) is a behavioural procedure in which preexposure to a stimulus not followed by reinforcement retards subsequent conditioning to this stimulus when it is paired with reinforcement. Changes in LI thus reflect greater or lesser retardation of learning which essentially implies a potentiation or an attenuation of the LI effect. LI has proved sensitive to psychotomimetic and antipsychotic treatment, which has encouraged its use to model learning and attention deficits in schizophrenia. In the present study, experiments were conducted to evaluate the effects of the psychotomimetic drug, phencyclidine (PCP, 2 mg/kg), and compare it with D-amphetamine (D-AMP, 0.33 and 1 mg/kg), on LI using a conditioned taste aversion procedure. PCP was found to potentiate LI when administered acutely prior to the conditioning trails, while no such effect was observed when administered prior to the preexposure trials. D-AMP, on the other hand, disrupted LI possibly due to a failure to induce a persistent taste aversion conditioning.
36.	Rahmathullah, Abu Sajana, 1986, et al. (författare) Merging-based forward-backward smoothing on Gaussian mixtures 2014 Ingår i: 17th International Conference on Information Fusion, FUSION 2014; Salamanca; Spain; 7 July 2014 through 10 July 2014. - 9788490123553 ; , s. - Konferensbidrag (refereegranskat)abstract Conventional forward-backward smoothing (FBS) for Gaussian mixture (GM) problems are based on pruning methods which yield a degenerate hypothesis tree and often lead to underestimated uncertainties. To overcome these shortcomings, we propose an algorithm that is based on merging components in the GM during filtering and smoothing. Compared to FBS based on the N-scan pruning, the proposed algorithm offers better performance in terms of track loss, root mean squared error (RMSE) and normalized estimation error squared (NEES) without increasing the computational complexity.
37.	Rahmathullah, Abu Sajana, 1986, et al. (författare) Smoothed probabilistic data association filter 2013 Ingår i: FUSION 2013, 9-12 July 2013, Istanbul, Turkey. - 9786058631113 ; , s. 1296 - 1303 Konferensbidrag (refereegranskat)abstract This paper presents the Smoothed Probabilistic Data Association Filter (SmPDAF) that attempts to improve the Gaussian approximations used in the Probabilistic Data Association Filter (PDAF). This is achieved by using information from future measurements. Newer approximations of the densities are obtained by using a combination of expectation propagation, which provides the backward likelihood information from the future measurements, and pruning, which uses these backward likelihoods to reduce the number of components in the Gaussian mixture. Performance comparison between SmPDAF and PDAF shows us that the root mean squared error performance of SmPDAF is significantly better than PDAF under comparable track loss performance.
38.	Rahmathullah, Abu Sajana, 1986, et al. (författare) Two-filter Gaussian mixture smoothing with posterior pruning 2014 Ingår i: 17th International Conference on Information Fusion, FUSION 2014, Salamanca, Spain, 7-10 July 2014. - 9788490123553 ; , s. Art. no. 6916249- Konferensbidrag (refereegranskat)abstract In this paper, we address the problem of smoothing on Gaussian mixture (GM) posterior densities using the two-filter smoothing (TFS) strategy. The structure of the likelihoods in the backward filter of the TFS is analysed in detail. These likelihoods look similar to GMs, but are not proper density functions in the state-space since they may have constant value in a subspace of the state space. We present how the traditional GM reduction techniques can be extended to this kind of GMs. We also propose a posterior-based pruning strategy, where the filtering density can be used to make further approximations of the likelihood in thebackward filter. Compared to the forward–backward smoothing(FBS) method based on N-scan pruning approximations, the proposed algorithm is shown to perform better in terms of track loss, normalized estimation error squared (NEES), computational complexity and root mean squared error (RMSE).
39.	Svensson, Daniel, 1979, et al. (författare) A New Multiple Model Filter with Switch Time Conditions 2010 Ingår i: IEEE Transactions on Signal Processing. - 1941-0476 .- 1053-587X. ; 58:1, s. 11-25 Tidskriftsartikel (refereegranskat)abstract The interacting multiple model filter has long been the method of choice for performing target tracking using multiple motion models. The filter finds a suboptimal solution to a problem which has the implicit assumption that immediate model shifts have the highest probability. When the sampling rate of the underlying continuous process is high compared to the target dynamics, this is not a reasonable assumption. Instead, changes in dynamics persist for some time. In this paper we propose an alternative switching model, which forces the dynamic models to persist for at least a model-specific time. The model is semi-Markov in nature, with a sojourn time probability mass function which is zero for a model-specific number of time steps, and then follows a geometrical distribution. Through this assumption a less complex problem in terms of model hypotheses arises, and to that problem we derive a state estimation algorithm that is close to optimal when the model assumptions are valid. Three other semi-Markov-based multiple-model filters are discussed and compared to in a qualitative sense. We also derive a new aircraft motion model for start and termination of turns. Finally, the proposed filter is evaluated on a benchmark scenario for tracking, and the results show a performance increase compared to the Interacting Multiple Model (IMM) filter for the trajectories considered.
40.	Svensson, Daniel, 1979, et al. (författare) An Alternative Derivation of the Cardinalized Probability Hypothesis Density Filter 2008 Rapport (övrigt vetenskapligt/konstnärligt)abstract In this report, an alternative approach to derive the Gaussian mixture cardinalized probability hypothesis density (GM-CPHD) filter is presented. The derivations differ in that the presented ones are based on "ordinary" statistics, while the original GM-CPHD derivation started from the finite set statistics (FISST) description of the CPHD filter. The results of the derivations are compared with filter update equations presented in another paper. The sets of equations are not completely equivalent. However, initial performance evaluations of the approaches indicate similar performance. Future work is needed to understand the differences between different GM-CPHD filter equations.
41.	Svensson, Daniel, 1979, et al. (författare) Performance Evaluation of MHT and GM-CPHD in a Ground Target Tracking Scenario 2009 Ingår i: Proceedings of the 12th International Conference on Information Fusion. - 9780982443804 ; , s. 300-307 Konferensbidrag (refereegranskat)abstract Performance evaluations of multi-target tracking algorithms are often limited to consider comparisons within the same algorithm family. In this paper, two conceptually different multi-target tracking algorithms are evaluated, namely a multiple-hypothesis tracking (MHT) algorithm and the Gaussian mixture cardinalized probability hypothesis density (GM-CPHD) filter. As a reference, a conventional single-hypothesis tracking algorithm is included in the evaluation. The performance is assessed using the root-mean square error of the estimated number of targets, and the recently published optimal subpattern assignment (OSPA) measure. The scenario under consideration is tracking of nine closely spaced ground targets, using simulated measurements from an airborne radar. By observing the estimation of the number of targets, as well as of the target states, conclusions are drawn regarding the behavior of MHT and GM-CPHD. For example, GM-CPHD is more responsive to changes in the number of targets, whereas MHT is less responsive, but produces a more stable output.
42.	Svensson, Daniel, 1979, et al. (författare) The multitarget Set JPDA filter with target identity 2011 Ingår i: Proceedings of SPIE: Signal Processing, Sensor Fusion, and Target Recognition XX. Conference on Signal Processing, Sensor Fusion, and Target Recognition XX Orlando, FL, APR 25-27, 2011. - : SPIE. - 0277-786X. - 9780819486240 ; 8050 Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract The Set JPDA (SJPDA) filter is a recently developed multi-target tracking filter that utilizes the relationbetween the density of a random finite set and the ordinary density of a state vector to improve on the JointProbabilistic Data Association (JPDA) filter. One advantage to the filter is the improved accuracy of the Gaussianapproximations of the JPDA, which result in avoidance of track coalescence. In the original presentation of theSJPDA filter, the focus was on problems where target identity is not relevant, and it was shown that the filterperforms better than the JPDA filter for such problems. The improved performance of the SJPDA is due toits relaxation of the labeling constraint that hampers most tracking approaches. However, if track identity isof interest a record of it may be kept even with a label-free approach such as the SJPDA: label-free targets arelocalized via the SJPDA, and then the identities are recalled as an overlay.
43.	Svensson, Daniel, 1979, et al. (författare) The Set IMMJPDA filter for multitarget tracking 2011 Ingår i: Proceedings of SPIE: Signal Processing, Sensor Fusion, and Target Recognition XX. Conference on Signal Processing, Sensor Fusion, and Target Recognition XX Orlando, FL, APR 25-27, 2011. - : SPIE. - 0277-786X. - 9780819486240 ; 8050 Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract The Set JPDA (SJPDA) filter is a recently developed multi-target tracking filter that utilizes the relationbetween the density of a random finite set and the ordinary density of a state vector to improve on the JointProbabilistic Data Association (JPDA) filter. One advantage to the filter is the improved accuracy of theGaussian approximations of the JPDA, which results in avoidance of track coalescence. Another advantage is animproved estimation accuracy in terms of a measure which disregards target identity. In this paper we extend thefilter to also consider multiple motion models. As a basis for the extension we use the Interacting Multiple Model(IMM) algorithm. We derive three alternative filters that we jointly refer to as Set IMMJPDA (SIMMJPDA).They are based on two alternative descriptions of the IMMJPDA filter. In the paper, we also present simulationresults for a two-target tracking scenario, which show improved tracking performance for the Set IMMJPDAfilter when evaluated with a measure that disregards target identity.
44.	Svensson, Lennart, 1976, et al. (författare) A New motion model for tracking of vehicles 2006 Ingår i: Proc. 14th IFAC Symposium on System Identification, SYSID 2006. Konferensbidrag (refereegranskat)abstract Accurate vehicle motion models are of essential importance for moderncar safety systems, as they enable more precise tracking and prediction of thetra±c. During normal driving, the driver controls the vehicle almost completely,yet, standard models, such as the constant acceleration kinematic model, fail toacknowledge the impact of the driver. In this paper, we propose a modi¯ed versionof the above mentioned model, in which the e®ect of the driver is introducedas an additional acceleration. To calculate this acceleration, we approximate thedriver with an optimal regulator, and derive an optimal trajectory through whichthe acceleration can be found. Our de¯nition of an optimal trajectory, is suchthat resulting path should be both comfortable, safe, fast and legal. Simulationsindicate that the new model can lead to signi¯cant gains in both tracking andprediction performance.
45.	Svensson, Lennart, 1976, et al. (författare) Multiple Model Filtering with Switch Time Conditions 2007 Ingår i: Proceedings of the 10th International Conference on Information Fusion. Konferensbidrag (refereegranskat)abstract The interacting multiple model filter has long been the preferred method to handle multiple models in target tracking. The filter finds a suboptimal solution to a problem, which implicitly assumes that immediate model shifts have the highest probability. We argue that this model-shift property does not capture the typical nature of maneuvering targets, namely that changes in target dynamics persist for some time. In this paper, we propose an adjusted switch time assumption that forces the dynamic models to remain fixed for a specified time. The modified filtering problem has lower complexity, and we derive a state estimation algorithm that is close to optimal in many scenarios. From Monte Carlo simulations, the new filter is found to yield a 20% decrease in root mean square position error, compared to the interacting multiple model filter in situations where the switch-time conditions are fulfilled.
46.	Svensson, Lennart, et al. (författare) ProViz : a tool for explorative 3-D visualization and template matching in electron tomograms 2017 Ingår i: Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization. - : Taylor & Francis. - 2168-1163 .- 2168-1171. ; 5:6, s. 446-454 Tidskriftsartikel (refereegranskat)abstract Visual understanding is a key aspect when studying electron tomography data-sets, aside quantitative assessments such as registration of high-resolution structures. We here present the free software tool ProViz (Protein Visualization) for visualisation and template matching in electron tomograms of biological samples. The ProViz software contains methods and tools which we have developed, adapted and computationally optimised for easy and intuitive visualisation and analysis of electron tomograms with low signal-to-noise ratio. ProViz complements existing software in the application field and serves as an easy and convenient tool for a first assessment and screening of the tomograms. It provides enhancements in three areas: (1) improved visualisation that makes connections as well as intensity differences between and within objects or structures easier to see and interpret, (2) interactive transfer function editing with direct visual result feedback using both piecewise linear functions and Gaussian function elements, (3) computationally optimised template matching and tools to visually assess and interactively explore the correlation results. The visualisation capabilities and features of ProViz are demonstrated on various biological volume data-sets: bacterial filament structures in vitro, a desmosome and the transmembrane cadherin connections therein in situ, and liposomes filled with doxorubicin in solution. The explorative template matching is demonstrated on a synthetic IgG data-set.
47.	Svensson, Lennart, 1976, et al. (författare) Set JPDA algorithm for tracking unordered sets of targets 2009 Ingår i: Proceedings of the 12th International Conference on Information Fusion. - 9780982443804 ; , s. 1187-1194 Konferensbidrag (refereegranskat)abstract In this article we show that traditional tracking algorithms should be adjusted when the objective is to recursively estimate an unordered (unlabeled) set of target state vectors, i.e., when it is not of importance to try to preserve target identities over time. We study scenarios where the number of targets is known, and propose a new version of the joint probabilistic data association (JPDA) filter that we call set JPDA (SJPDA). Simulations show that the new filter outperforms the JPDA in a two-target scenario when evaluated according to the mean optimal subpattern assignment (MOSPA) measure.
48.	Svensson, Lennart, 1976, et al. (författare) Set JPDA Filter for Multi-Target Tracking 2010 Rapport (övrigt vetenskapligt/konstnärligt)abstract In this report we show that when targets are closely spaced, traditional trackingalgorithms can be adjusted to perform better under a performance measure thatdisregards identity. More specifically, we propose an adjusted version of the JointProbabilistic Data Association (JPDA) filter, which we call Set JPDA (SJPDA).Through examples and theory we motivate the new approach, and show its possibilities.To decrease the computational requirements, we further show that the SJPDAfilter can be formulated as a continuous optimization problem which is fairly easy tohandle. Optimal approximations are also discussed, and an algorithm, KLSJPDA,which provides optimal Gaussian approximations in the Kullback-Leibler sense isderived. Finally, we evaluate the SJPDA filter on two scenarios with closely spacedtargets, and compare the performance in terms of the mean Optimal SubpatternAssignment (MOSPA) measure with the JPDA filter, and also with the GaussianmixtureCPHD filter. The results show that the SJPDA filter performs substantiallybetter than the JPDA filter, and almost as well as the more complex GM-CPHDfilter.
49.	Svensson, Lennart, 1976, et al. (författare) Set JPDA Filter for Multitarget Tracking 2011 Ingår i: IEEE Transactions on Signal Processing. - 1941-0476 .- 1053-587X. ; 59:10, s. 4677-4691 Tidskriftsartikel (refereegranskat)abstract In this article, we show that when targets are closelyspaced, traditional tracking algorithms can be adjusted to performbetter under a performance measure that disregards identity.More specifically, we propose an adjusted version of the jointprobabilistic data association (JPDA) filter, which we call setJPDA (SJPDA). Through examples and theory we motivate thenew approach, and show its possibilities. To decrease the computationalrequirements, we further show that the SJPDA filter can beformulated as a continuous optimization problem which is fairlyeasy to handle. Optimal approximations are also discussed, and analgorithm, Kullback–Leibler SJPDA (KLSJPDA), which providesoptimal Gaussian approximations in the Kullback–Leibler senseis derived. Finally, we evaluate the SJPDA filter on two scenarioswith closely spaced targets, and compare the performance in termsof the mean optimal subpattern assignment (MOSPA) measurewith the JPDA filter, and also with the Gaussian-mixture cardinalizedprobability hypothesis density (GM-CPHD) filter. The resultsshow that the SJPDA filter performs substantially better than theJPDA filter, and almost as well as the more complex GM-CPHDfilter.
50.	Wass, Caroline, 1976, et al. (författare) Effects of phencyclidine on spatial learning and memory: nitric oxide-dependent mechanisms 2006 Ingår i: Behav Brain Res. ; 171:1, s. 147-53 Tidskriftsartikel (refereegranskat)abstract Cognitive deficits of schizophrenia constitute a disabling part of the disease predicting treatment success as well as functional outcome. Phencyclidine (PCP), a non-competitive NMDA receptor antagonist was used to model schizophrenic cognitive dysfunctions of learning and memory using the Morris water maze paradigm for reference memory. In experiment 1 male Sprauge-Dawley rats were acutely administered PCP (0.5, 1.0 and 2.0 mg/kg s.c.) before the first swim session on each of the four acquisition days. Probe test for reference memory was performed 2 days after the last acquisition day; the first probe without drug treatment to assess reference memory and a second probe with prior drug treatment to control for state dependency effects of PCP. In experiment 2 the effects of pre-treatment (10 min before PCP) with the nitric oxide synthase inhibitor, L-NAME (10 mg/kg s.c.), on the PCP (2 mg/kg)-induced spatial memory deficit was evaluated in the Morris water maze paradigm for reference memory. The results showed that PCP in a dose of 2 mg/kg disrupts spatial learning as estimated by prolonged search time to find platform during acquisition as well as the reference memory test as measured by less time spent in target quadrant during probe trial. No state dependency effects of PCP were found. Pre-treatment with L-NAME completely reversed the PCP-induced disruption of acquisition learning. The reference memory disruption was, however, not completely restored as measured by probe trial.

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