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1.	Glentis, G. -O, et al. (författare) Efficient spectral analysis in the missing data case using sparse ML methods 2014 Ingår i: European Signal Processing Conference. - 2219-5491. Konferensbidrag (refereegranskat)abstract Given their wide applicability, several sparse high-resolution spectral estimation techniques and their implementation have been examined in the recent literature. In this work, we further the topic by examining a computationally efficient implementation of the recent SMLA algorithms in the missing data case. The work is an extension of our implementation for the uniformly sampled case, and offers a notable computational gain as compared to the alternative implementations in the missing data case.
2.	Adalbjörnsson, Stefan Ingi, et al. (författare) High resolution sparse estimation of exponentially decaying two-dimensional signals 2014 Ingår i: European Signal Processing Conference. - 2219-5491. Konferensbidrag (refereegranskat)abstract In this work, we consider the problem of high-resolution estimation of the parameters detailing a two-dimensional (2-D) signal consisting of an unknown number of exponentially decaying sinusoidal components. Interpreting the estimation problem as a block (or group) sparse representation problem allows the decoupling of the 2-D data structure into a sum of outer-products of 1-D damped sinusoidal signals with unknown damping and frequency. The resulting non-zero blocks will represent each of the 1-D damped sinusoids, which may then be used as non-parametric estimates of the corresponding 1-D signals; this implies that the sought 2-D modes may be estimated using a sequence of 1-D optimization problems. The resulting sparse representation problem is solved using an iterative ADMM-based algorithm, after which the damping and frequency parameter can be estimated by a sequence of simple 1-D optimization problems.
3.	Adalbjörnsson, Stefan Ingi, et al. (författare) Sparse Estimation Of Spectroscopic Signals 2011 Ingår i: European Signal Processing Conference. - 2219-5491. ; 2011, s. 333-337 Konferensbidrag (refereegranskat)abstract This work considers the semi-parametric estimation of sparse spec- troscopic signals, aiming to form a detailed spectral representation of both the frequency content and the spectral line widths of the oc- curring signals. Extending on the recent FOCUSS-based SLIM al- gorithm, we propose an alternative prior for a Bayesian formulation of this sparse reconstruction method, exploiting a proposed suitable prior for the noise variance. Examining three common models for spectroscopic signals, the introduced technique allows for reliable estimation of the characteristics of these models. Numerical sim- ulations illustrate the improved performance of the proposed tech- nique.
4.	Akesson, Maria, et al. (författare) Highly Accurate and Noise-Robust Phase Delay Estimation using Multitaper Reassignment 2023 Ingår i: 31st European Signal Processing Conference, EUSIPCO 2023 - Proceedings. - 2219-5491. - 9789464593600 ; , s. 1763-1767 Konferensbidrag (refereegranskat)abstract The recently developed Phase-Scaled Reassignment (PSR) can estimate phase-difference between two oscillating transient signals with high accuracy. However, in low signal-to-noise ratios (SNRs) the performance of commonly applied reassignment techniques is known to deteriorate. In order to reduce variance in low SNR, we propose a multitaper PSR (mtPSR) method for phase-difference estimation between Gaussian transient signals. Three possible variations of this method are investigated and evaluated, mtPSR1, mtPSR2, and mtPSR3. All three variations are shown to outperform state-of-the-art methods and improve estimation accuracy in low SNR. The mtPSR1 is superior in terms of computational efficiency while the mtPSR3 achieves the highest accuracy. The mtPSR technique is also shown to be robust to model assumptions. An example of phase delay estimates of the electrical signals measured from the brain reveals promising results.
5.	Akesson, Maria, et al. (författare) Phase Reassignment with Efficient Estimation of Phase Difference 2022 Ingår i: 30th European Signal Processing Conference, EUSIPCO 2022 - Proceedings. - 2219-5491. - 9789082797091 ; 2022-August, s. 2126-2130 Konferensbidrag (refereegranskat)abstract The recently developed Matched Phase Reassignment (MPR) gives a time-frequency local measure of phase difference between short oscillatory transient signals. However, the resulting phase estimate is not satisfactory as it has poor resolution for high oscillatory frequencies. The MPR is also sensitive to high noise levels and is computationally cumbersome. In this paper, a novel reassignment method for phase difference estimation is proposed and evaluated. In comparison to the MPR the accuracy is increased and the computational time is reduced. Simulations show that the proposed technique also outperforms state-of-the-art methods in terms of efficiency. An illustrative example of phase difference estimates of the electrical signals measured from the brain is included.
6.	Andersson, Matilda, et al. (författare) Augmentation Strategies for Self-Supervised Representation Learning from Electrocardiograms 2023 Ingår i: 31st European Signal Processing Conference, EUSIPCO 2023 - Proceedings. - 2219-5491. - 9789464593600 ; , s. 1075-1079 Konferensbidrag (refereegranskat)abstract In this paper, we investigate the effects of different augmentation strategies in self-supervised representation learning from electrocardiograms. Our study examines the impact of random resized crop and time out on downstream performance. We also consider the importance of the signal length. Furthermore, instead of using two augmented copies of the sample as a positive pair, we suggest augmenting only one. The second signal is kept as the original signal. These different augmentation strategies are investigated in the context of pre-training and fine-tuning, following the different self-supervised learning frameworks BYOL, SimCLR, and VICReg. We formulate the downstream task as a multi-label classification task using a public dataset containing ECG recordings and annotations. In our experiments, we demonstrate that self-supervised learning can consistently outperform classical supervised learning when configured correctly. These findings are of particular importance in the medical domain, as the medical labeling process is particularly expensive, and clinical ground truth is often difficult to define. We are hopeful that our findings will be a catalyst for further research into augmentation strategies in self-supervised learning to improve performance in the detection of cardiovascular disease.
7.	Angelopoulos, Kostas, et al. (författare) Efficient Time Recursive Coherence Spectrum Estimation 2012 Ingår i: Signal Processing Conference (EUSIPCO), 2012 Proceedings of the 20th European. - 2076-1465 .- 2219-5491. - 9781467310680 ; , s. 425-429 Konferensbidrag (refereegranskat)abstract The coherence spectrum is of notable interest as a bivariate spectral measure in a variety of application, and the topic has lately attracted notable interest with the recent formulation of several high-resolution data adaptive estimators. In this work, we present computationally efficient time recursive implementations of the recent iterative adaptive approach (IAA) estimator, examining both the case of complete data sets and when some observations are missing. The algorithms continues the recent development of exploiting the estimators’ inherently low displacement rank of the necessary products of Toeplitz-like matrices, extending these to time-updating formulations for the IAA-based coherence estimation algorithm. Numerical simulations together with theoretical complexity measures illustrate the performance of the proposed algorithm.
8.	Ask, Erik, et al. (författare) A Unifying Approach to Minimal Problems in Collinear and Planar TDOA Sensor Network Self-Calibration 2014 Ingår i: European Signal Processing Conference. - 2219-5491. Konferensbidrag (refereegranskat)abstract This work presents a study of sensor network calibration from time-difference-of-arrival (TDOA) measurements for cases when the dimensions spanned by the receivers and the transmitters differ. This could for example be if receivers are restricted to a line or plane or if the transmitting objects are moving linearly in space. Such calibration arises in several applications such as calibration of (acoustic or ultrasound) microphone arrays, and radio antenna networks. We propose a non-iterative algorithm based on recent stratified approaches: (i) rank constraints on modified measurement matrix, (ii) factorization techniques that determine transmitters and receivers up to unknown affine transformation and (iii) determining the affine stratification using remaining non-linear constraints. This results in a unified approach to solve almost all minimal problems. Such algorithms are important components for systems for self-localization. Experiments are shown both for simulated and real data with promising results.
9.	Aström, Kalle, et al. (författare) Extension of Time-Difference-of-Arrival Self Calibration Solutions Using Robust Multilateration 2021 Ingår i: 29th European Signal Processing Conference, EUSIPCO 2021 - Proceedings. - 2076-1465 .- 2219-5491. - 9789082797060 ; , s. 870-874 Konferensbidrag (refereegranskat)abstract Recent advances in robust self-calibration have made it possible to estimate microphone positions and at least partial sound source positions using ambient sound. However, there are limits on how well sound source paths can be recovered using state-of-the-art techniques. In this paper we develop and evaluate several techniques to extend partial and incomplete solutions. We present minimal solvers for sound source positioning using non-overlapping pairs of microphone positions and their respective time-difference measurements, and show how these new solvers can be used in a hypothesis and test setting. We also investigate techniques that exploit temporal smoothness of the sound source paths. The different techniques are evaluated on both real and synthetic data, and compared to several state-of-the-art techniques for time-difference-of-arrival multilateration.
10.	Björk, Marcus, 1985-, et al. (författare) Signal Processing Algorithms for Removing Banding Artifacts in MRI 2011 Ingår i: Proceedings of the 19th European Signal Processing Conference (EUSIPCO-2011). ; , s. 1000-1004, s. 1000-1004 Konferensbidrag (refereegranskat)abstract In magnetic resonance imaging (MRI), the balanced steady-state free precession (bSSFP) pulse sequence has shown to be of great interest, due to its relatively high signal-to-noise ratio in a short scan time. However, images acquired with this pulse sequence suffer from banding artifacts due to off-resonance effects. These artifacts typically appear as black bands covering parts of the image and they severely degrade the image quality. In this paper, we present a fast two-step algorithm for estimating the unknowns in the signal model and removing the banding artifacts. The first step consists of rewriting the model in such a way that it becomes linear in the unknowns (this step is named Linearization for Off-Resonance Estimation, or LORE). In the second step, we use a Gauss-Newton iterative optimization with the parameters obtained by LORE as initial guesses. We name the full algorithm LORE-GN. Using both simulated and in vivo data, we show the performance gain associated with using LORE-GN as compared to general methods commonly employed in similar cases.
11.	Brynolfsson, Johan, et al. (författare) Multitaper Estimation of the Coherence Spectrum in low SNR 2014 Ingår i: European Signal Processing Conference. - 2219-5491. Konferensbidrag (refereegranskat)abstract A pseudo coherence estimate using multitapers is presented. The estimate has better localization for sinusoids and is shown to have lower variance for disturbances compared to the usual coherence estimator. This makes it superior in terms of finding coherent frequencies between two sinusoidal signals; even when observed in low SNR. Different sets of multitapers are investigated and the weights of the final coherence estimate are adjusted for a low-biased estimate of a single sinusoid. The proposed method is more computationally efficient than data dependent methods, and does still give comparable results.
12.	Faundez-Zanuy, M., et al. (författare) On the relevance of bandwidth extension for speaker identification 2015 Ingår i: European Signal Processing Conference. - : EUSIPCO. - 2219-5491. Tidskriftsartikel (refereegranskat)abstract In this paper we discuss the relevance of bandwidth extension for speaker identification tasks. Mainly we want to study if it is possible to recognize voices that have been bandwith extended. For this purpose, we created two different databases (microphonic and ISDN) of speech signals that were bandwidth extended from telephone bandwidth ([300, 3400] Hz) to full bandwidth ([100, 8000] Hz). We have evaluated different parameterizations, and we have found that the MELCEPST parameterization can take advantage of the bandwidth extension algorithms in several situations.
13.	Fernandez, Joel, et al. (författare) Linearization of Active Array Transmitters Under Crosstalk via Over-the-Air Observations 2023 Ingår i: European Signal Processing Conference. - 2219-5491. ; , s. 1420-1424 Konferensbidrag (refereegranskat)abstract Finding computationally feasible solutions to linearize active antenna array transmitters is a timely challenge in modern cellular networks, particularly in 5G and the emerging 6G systems. In this paper, we propose a new modeling and parameter estimation approach to characterize the individual power amplifier (PA) units of an active antenna array subject to crosstalk while relying only on over-the-air observations. Additionally, we describe a beam-sweeping based forward model learning procedure and the corresponding closed-loop digital predistortion (DPD) learning algorithm, to efficiently linearize millimeter-wave phased-array transmitters under crosstalk-induced load modulation. The provided numerical results demonstrate excellent parameter estimation and linearization performance, reaching adjacent channel power ratios (ACPRs) as low as -50 to -60 dB with realistic evaluation assumptions.
14.	Ferranti, Luca, et al. (författare) Homotopy Continuation for Sensor Networks Self-Calibration 2021 Ingår i: 29th European Signal Processing Conference, EUSIPCO 2021 - Proceedings. - 2219-5491. - 9789082797060 ; 2021-August, s. 1725-1729 Konferensbidrag (refereegranskat)abstract Given a sensor network, TDOA self-calibration aims at simultaneously estimating the positions of receivers and transmitters, and transmitters time offsets. This can be formulated as a system of polynomial equations. Due to the elevated number of unknowns and the nonlinearity of the problem, obtaining an accurate solution efficiently is nontrivial. Previous work has shown that iterative algorithms are sensitive to initialization and little noise can lead to failure in convergence. Hence, research has focused on algebraic techniques. Stable and efficient algebraic solvers have been proposed for some network configurations, but they do not work for smaller networks. In this paper, we use homotopy continuation to solve four previously unsolved configurations in 2D TDOA self-calibration, including a minimal one. As a theoretical contribution, we investigate the number of solutions of the new minimal configuration, showing this is much lower than previous estimates. As a more practical contribution, we also present new subminimal solvers, which can be used to achieve unique accurate solutions in previously unsolvable configurations. We demonstrate our solvers are stable both with clean and noisy data, even without nonlinear refinement afterwards. Moreover, we demonstrate the suitability of homotopy continuation for sensor network calibration problems, opening prospects to new applications.
15.	Ferreol, A., et al. (författare) A New Expression of the Asymptotic Performances of Maximum Likelihood DOA Estimation Method With Modeling Errors 2004 Ingår i: Proceeding EURASIP 2004, Vienna, Austria.. - 2219-5491. - 9783200001657 ; , s. 2163-2166 Konferensbidrag (refereegranskat)abstract This paper provides a new analytic expression of the RMS (Root Mean Square) error and bias of the Maximum Likelihood (ML) Direction Of Arrival (DOA) estimator in the presence of steering vectors modeling errors. The reference [4] proposes a first order approximation of these performances which is adapted to small modeling errors. In order to take into account larger modeling errors and provide tools for designing experimental set-up, a more accurate and easily usable derivation of these performances is necessary For such an investigation, the DOA estimation errors are written as an hermitean form with a stochastic vector composed by the modeling errors. Finally, a closed form expression between the performances (bias and RMS error) and statistical moments of the model error are deduced from the statistics of the hermitean form. Simulations confirm the theoretical results.
16.	Ferreol, A., et al. (författare) Modeling error sensitivity of the MUSIC algorithm conditioned on resolved sources 2008 Ingår i: European Signal Processing Conference. - 2219-5491. Konferensbidrag (refereegranskat)abstract When the correlation matrix is known, the resolution power of subspace algorithms is infinite. In the presence of modelling errors, even if the correlation matrix is known, sources can no longer be resolved with certainty. Focusing on the MUSIC algorithm [1], the purpose of this work is to provide closed form expression of bias and variance versus the model mismatch (these errors can be different for each source). Un-like previous work, these performance measures are derived conditioned on the success of a certain source resolution test. Among the resolution definitions proposed in [2], we investigate which one is more suitable for our purposes. Numerical results support the theoretical investigations. Our findings are of a great interest for the determination of the necessary antenna calibration accuracy to achieve specifications on the estimator performance.
17.	Garcia, Guillermo, 1976, et al. (författare) A Methodology for speaker-dependent acoustic features based on a simplified cortical response for speaker verification systems 2009 Ingår i: 17th European Signal Processing Conference, EUSIPCO 2009; Glasgow; United Kingdom; 24 August 2009 through 28 August 2009. - 2219-5491. ; , s. 1240-1243 Konferensbidrag (refereegranskat)abstract Recently, the incorporation of the research done in biologically inspiredsystems has shown satisfactory results. A promising researcharea is the understanding of the human auditory systems and itsperformance under noisy conditions. Moreover, the incorporationof brain functions (cortical response) as an active part of the auditorysystem seems a viable alternative to increase the robustness ofspeech and speaker recognition systems. In this study, we proposea simplified model of the mammalian central auditory system forspeaker verification systems. This model is based on a dimension expansionrepresentation, attempting to capture the response of thecortical cells. Then, by means of the Principal Component Analysis(PCA) approach, we reduce the dimensionality and create speakerdependentfeatures. Our results showed that by using our modelingtechnique, we were able to improve the performance of speaker verificationsystems.
18.	Garcia, Guillermo, 1976, et al. (författare) Sample iterative likelihood maximization for speaker verification systems 2010 Ingår i: 18th European Signal Processing Conference, EUSIPCO 2010; Aalborg; Denmark; 23 August 2010 through 27 August 2010. - 2219-5491. ; , s. 596-600 Konferensbidrag (refereegranskat)abstract Gaussian Mixture Models (GMMs) have been the dominant technique used for modeling in speaker recognition systems. Traditionally, the GMMs are trained using the Expectation Maximization (EM) algorithm and a large set of training samples. However, the convergence of the EM algorithm to a global maximum is conditioned on proper parameter initialization, a large enough training sample set, and several iterations over this training set. In this work, a Sample Iterative Likelihood Maximization (SILM) algorithm based on a stochastic descent gradient method is proposed. Simulation results showed that our algorithm can attain high loglikelihoods with fewer iterations in comparison to the EMalgorithm. A maximum of eight times faster convergence rate can be achieved in comparison with the EM algorithm.
19.	Garcia, Guillermo, 1976, et al. (författare) Study of mutual information for speaker recognition features 2010 Ingår i: 18th European Signal Processing Conference, EUSIPCO 2010; Aalborg; Denmark; 23 August 2010 through 27 August 2010. - 2219-5491. ; , s. 601-605 Konferensbidrag (refereegranskat)abstract Feature extraction is an important stage in speaker recognition systems since the overall performance depends on the type of the extracted features. In the framework of speaker recognition, the extracted features are mainly based on transformations of the speech spectrum. In spite of the great variety of features extracted from the speech, the common empirical approach to select features is based on a complete performance evaluation of the system. In this paper, we propose an information theory approach to evaluate the information about the speaker identity contained on the speech features. The results show that this approach can help on a more efficient feature selection. We also present an alternative AMFMbased magnitude representation of the speech that attains better performance than the MFCCs. Moreover, we show that phase information features can perform well in speaker verification systems.
20.	Glentis, George-Othan, et al. (författare) Preconditioned Conjugate Gradient IAA Spectral Estimation 2011 Ingår i: European Signal Processing Conference. - 2219-5491. ; 2001, s. 1195-1199 Konferensbidrag (refereegranskat)abstract In this paper, we develop superfast approximative algorithms for the computationally efficient implementation of the recent Iterative Adaptive Approach (IAA) spectral estimate. The proposed methods are based on rewriting the IAA algorithm using suitable Gohberg-Semencul representations, solving the resulting linear systems of equations using the preconditioned conjugate gradient method, where a novel preconditioning is applied using an incomplete factorization of the Toeplitz matrix. Numerical simulations illustrate the efficiency of the proposed algorithm.
21.	Jansson, Andreas, et al. (författare) Range-based radar model structure selection 2021 Ingår i: 28th European Signal Processing Conference, EUSIPCO 2020 - Proceedings. - 2219-5491. - 9789082797053 ; 2021-January, s. 2269-2273 Konferensbidrag (refereegranskat)abstract In this work, we study under which circumstances it is appropriate to use simplified models for range determination using radar. Typically, pulsed radar systems result in the backscattered, demodulated, and matched signal having a chirp signal structure, with the frequency rate being related to the range to the reflecting target and the relative velocity of the transmitter and reflector. Far from the target, and at low relative velocities, one may achieve preferable location estimates by neglecting the frequency rate, treating the received signal as being purely sinusoidal, whereas at close range, neglecting the frequency rate notably reduces the achievable performance. Using misspecified estimation theory, we derive a lower bound of the achievable performance when neglecting the true signal structure, and show at which ranges one model is preferable to the other. Numerical results from a mm-wave radar system illustrate the results.
22.	Jensen, Jesper, et al. (författare) Computationally Efficient IAA-Based Estimation of the Fundamental Frequency 2012 Ingår i: Signal Processing Conference (EUSIPCO), 2012 Proceedings of the 20th European. - 2076-1465 .- 2219-5491. - 9781467310680 ; , s. 2163-2167 Konferensbidrag (refereegranskat)abstract Optimal linearly constrained minimum variance (LCMV) filtering methods have recently been applied to fundamental frequency estimation. Like many other fundamental frequency estimators, these methods are constructed using an estimate of the inverse data covariance matrix. The required matrix inverse is typically formed using the sample covariance matrix via data partitioning, although this is well-known to adversely affect the spectral resolution. In this paper, we propose a fast implementation of a novel optimal filtering method that utilizes the LCMV principle in conjunction with the iterative adaptive approach (IAA). The IAA formulation enables an accurate covariance matrix estimate from a single snapshot, i.e., without data partitioning, but the improvement comes at a notable computational cost. Exploiting the estimator's inherently low displacement rank of the necessary products of Toeplitz-like matrices, we form a computationally efficient implementation, reducing the required computational complexity with several orders of magnitude. The experimental results show that the performance of the proposed method is comparable or better than that of other competing methods in terms of spectral resolution.
23.	Juhlin, Maria, et al. (författare) Localization Of Multiple Jammers In Wireless Sensor Networks 2021 Ingår i: 29th European Signal Processing Conference, EUSIPCO 2021 - Proceedings. - 2219-5491. - 9789082797060 ; 2021-August, s. 1596-1600 Konferensbidrag (refereegranskat)abstract Wireless sensor networks are susceptible to jamming attacks that can result in communication breakdowns. Preemptive measures to prevent jamming attacks is an active research field, but to stop an ongoing attack often requires that one is able to locate jammers in order to neutralize them. Several methods exist for the case when the network is corrupted by a single jammer, although these generally do not allow for cases when more than one jammer is present. In this work, we introduce an iterative procedure that determines the number of jammers corrupting the network as part of the localization of the jammers. The performance of the method is illustrated using numerical examples.
24.	Juhlin, Maria, et al. (författare) Optimal microphone placement for localizing tonal sound sources 2021 Ingår i: 28th European Signal Processing Conference, EUSIPCO 2020 - Proceedings. - 2219-5491. - 9789082797053 ; 2021-January, s. 236-240 Konferensbidrag (refereegranskat)abstract This work is concerned with determining optimal microphone placements that allow for an accurate location estimate of the sound sources, taking into account the expected signal structure of voiced speech, as well as the expected location areas and the typical range of the fundamental frequencies of the speakers. To determine preferable microphone placements, we propose a scheme that minimizes a theoretical lower bound on the variance of the location estimates over the possible sensor placements, while taking into account the expected variability in the impinging signals. Numerical examples and real measurements illustrate the performance of the proposed scheme.
25.	Keding, Oskar, et al. (författare) Coherence Expectation Minimisation and Combining Weighted Multitaper Estimates 2023 Ingår i: 31st European Signal Processing Conference, EUSIPCO 2023 - Proceedings. - 2219-5491. - 9789464593600 ; , s. 1993-1997 Konferensbidrag (refereegranskat)abstract Coherence is a useful measure in many engineering applications. Here, we focus on the case where the input signal to a linear system can be measured free from noise, but the output signal is perturbed by noise. A novel expression for the expectation of a multitaper magnitude squared coherence estimate for this case is presented and verified through numerical evaluation. Additionally, the expression is used to optimise a multitaper coherence estimation method, which gives improved coherence estimation in detection. A clever combination of two weighted magnitude squared coherence multitaper estimators yields a new method, called Combined Weighted Multitaper Coherence (CWMC). The method is evaluated and compared to the Thomson multitaper method for simulated data and on real visual evoked potential electroencephalogram data, showing consistent improvement using CWMC.
26.	Keding, Oskar, et al. (författare) ROBUST PHASE DIFFERENCE ESTIMATION OF TRANSIENTS IN HIGH NOISE LEVELS 2022 Ingår i: 30th European Signal Processing Conference, EUSIPCO 2022 - Proceedings. - 2219-5491. - 9789082797091 ; 2022-August, s. 2271-2275 Konferensbidrag (refereegranskat)abstract This paper presents the Reassignment Vector Phase Difference Estimator (RVPDE), which gives noise robust relative phase estimates of oscillating transient signals in high noise levels. Estimation of relative phase information between signals is of interest for direction of arrival estimation, source separation and spatio-temporal decoding in neurology as well as for soundscape analysis. The RVPDE relies on the spectrogram reassignment vectors which contains information of the time-frequency local phase difference between two transient signals. The final estimate, which is robust to high noise levels, is given as the median over the local time-frequency area. The proposed technique is shown to outperform state-of-the-art methods in simulations for high noise levels. A discussion on the statistical distribution of the estimates is also presented, and finally an example of phase difference estimation of visually evoked potentials measured from electrical brain signals is shown.
27.	Klang, Göran, et al. (författare) Interference Rejection in Systems Employing Transmit Diversity 2002 Ingår i: European Signal Processing Conference. - : EUSIPCO. - 2219-5491. Tidskriftsartikel (refereegranskat)abstract Space diversity methods provide excellent means for increasing the robustness against interference and noise in communication systems. This is well known for systems using multiple receive antennas and it holdsforsystems applying transmit diversity as well. In fact, the use of transmit diversity provide two independent means for reducing the impact of interference. Via the diversity gain and via the code rate, both related to the underlying space-time code. In this paper, we are considering the use of space diversity methods in conjunction with interference rejection combining (IRC) to mitigate the impact of interference and noise for interference limited scenarios. Transmit diversity schemes based on space-time block codes (STBC) are assumed. We elucidate the importance of taking into account the spatio-temporal correlation induced by cochannel users employing transmit diversity. A novel space-time IRC (STIRC) scheme is proposed to handle the problem. The STIRC scheme combines the simplicity of conventional IRC while taking the structure of interfering users into account. Simulation examples demonstrate significant gains compared to the use of conventional IRC.
28.	Kronvall, Ted, et al. (författare) Joint DOA and Multi-Pitch Estimation Via Block Sparse Dictionary Learning 2014 Ingår i: European Signal Processing Conference. - 2219-5491. Konferensbidrag (refereegranskat)abstract In this paper, we introduce a novel sparse method for joint estimation of the direction of arrivals (DOAs) and pitches of a set of multi-pitch signals impinging on a sensor array. Extending on earlier approaches, we formulate a novel dictionary learning framework from which an estimate is formed without making assumptions on the model orders. The proposed method alternatively uses a block sparse approach to estimate the pitches, using an alternating direction method of multipliers framework, and alternatively a nonlinear least squares approach to estimate the DOAs. The preferable performance of the proposed algorithm, as compared to earlier methods, is shown using numerical examples.
29.	Kyriakidou, Georgia, et al. (författare) Improved modeling and bounds for NQR spectroscopy signals 2014 Ingår i: European Signal Processing Conference. - 2219-5491. Konferensbidrag (refereegranskat)abstract Nuclear Quadrupole Resonance (NQR) is a method of de- tection and unique characterization of compounds containing quadrupolar nuclei, commonly found in many forms of ex- plosives, narcotics, and medicines. Typically, multi-pulse sequences are used to acquire the NQR signal, allowing the resulting signal to be well modeled as a sum of exponentially damped sinusoidal echoes. In this paper, we improve upon the earlier used NQR signal model, introducing an observed amplitude modulation of the spectral lines as a function of the sample temperature. This dependency noticeably af- fects the achievable identification performance in the typical case when the substance temperature is not perfectly known. We further extend the recently presented Cramér-Rao lower bound to the more detailed model, allowing one to determine suitable experimental conditions to optimize the detection and identifiability of the resulting signal. The theoretical results are carefully motivated using extensive NQR measurements.
30.	Larsson, Malte, et al. (författare) Efficient Time-of-Arrival Self-Calibration using Source Implicitization 2023 Ingår i: 31st European Signal Processing Conference, EUSIPCO 2023 - Proceedings. - 2219-5491. - 9789464593600 ; , s. 1644-1648 Konferensbidrag (refereegranskat)abstract In this paper we revisit the Time-of-Arrival self-calibration problem. In particular we focus on imbalanced problem instances where there are significantly more sources compared to the number of receivers, which is a common configuration in real applications. Using an implicit representation, we are able to re-parameterize the sensor node self-calibration problem using only the parameters of the receiver positions. Making the source positions implicit, we show that it is possible to linearize the maximum-likelihood error around the measured distances, resulting in a Sampson-like approximation. Given four unknown receiver positions and a large number of unknown sender positions, we show that our formulation leads to algorithms for robust calibration, with significant speed-up compared to running the full optimization over all unknowns. The proposed method is tested on both synthetic and real data.
31.	McKelvey, Tomas, 1966 (författare) Auto-calibration of Uniform Linear Array Antennas 2019 Ingår i: European Signal Processing Conference. - 2219-5491. ; 2019-September Konferensbidrag (refereegranskat)abstract Calibration is instrumental to realize the full performance of a measurement system. In this contribution we consider the calibration of a uniformly linear array antenna where we assume each antenna element has an unknown complex gain. We present an algorithm which can be used to calibrate the array without full knowledge of the environment. Particularly, if the number of signal sources are known we show that we can determine the individual unknown antenna gains up to an ambiguity parametrized by a single complex scalar. If the ratio of the complex gains between two consecutive elements is also known, this ambiguity is resolved. The method is based on determining the antenna calibration parameters such that the Hankel matrix of the array snapshots has a given rank. A numerical example illustrates the performance of the method. The numerical results suggest that the method is consistent in SNR.
32.	Miri, Maliheh, et al. (författare) Brain fingerprinting using EEG graph inference 2023 Ingår i: 31st European Signal Processing Conference, EUSIPCO 2023 - Proceedings. - 2219-5491. - 9789464593600 ; , s. 1025-1029 Konferensbidrag (refereegranskat)abstract Taking advantage of the human brain functional connectome as an individual's fingerprint has attracted great research in recent years. Conventionally, Pearson correlation between regional time-courses is used as a pairwise measure for each edge weight of the connectome. Building upon recent advances in graph signal processing, we propose here to estimate the graph structure as a whole by considering all time-courses at once. Using data from two publicly available datasets, we show the superior performance of such learned brain graphs over correlation-based functional connectomes in characterizing an individual.
33.	Månsson, Anders, et al. (författare) Multidimensional Cramér-Rao Lower Bound for Non-uniformly Sampled NMR Signals 2014 Ingår i: European Signal Processing Conference. - 2219-5491. Konferensbidrag (refereegranskat)abstract In this work, we extend recent results on the Cramé r-Rao lower bound for multidimensional non-uniformly sampled Nuclear Magnetic Resonance (NMR) signals. The used signal model is more general than earlier models, allowing for the typically present variance differences between the direct and the dif- ferent indirect sampling dimensions. The presented bound is verified with earlier presented 1-and R-dimensional bounds as well as with the obtainable estimation accuracy using the statistically efficient non-linear least squares estimator. Finally, the usability of the presented bound is illustrated as a mea- sure of the obtainable accuracy using three different sampling schemes for a real 15N-HSQC NMR experiment.
34.	Månsson, Erik M., et al. (författare) The smoothed reassigned spectrogram for robust energy estimation 2021 Ingår i: 28th European Signal Processing Conference, EUSIPCO 2020 - Proceedings. - 2219-5491. - 9789082797053 ; 2021-January, s. 2210-2214 Konferensbidrag (refereegranskat)abstract The matched window reassigned spectrogram relocates all signal energy of an oscillating transient to the time- and frequency locations, resulting in a sharp peak in the time-frequency plane. However, previous research has shown that the method may result in split energy peaks for close components and in high noise levels, and the peak energy is then erroneously estimated. With use of novel knowledge on the statistics when subjected to noise, we propose a novel method, the smoothed reassigned spectrogram, for obtaining a stable and accurate measure of the signal energy from the peak value, with retained resolution properties. We also suggest a simple set of rules to enhance the reassigned spectrogram and speed up its calculation. Simulations are performed to verify the accuracy and an application example on radar data is shown.
35.	Olmos, Salvador, et al. (författare) Subspace detectors for multichannel signals 2015 Ingår i: European Signal Processing Conference. - 2219-5491. ; 2015-March Tidskriftsartikel (refereegranskat)abstract In this paper a multichannel subspace detector is proposed based on a separable spatio-temporal linear model. The generalized likelihood ratio test (GLRT) for this model is derived for the case of coloured Gaussian noise and known temporal and covariance matrices. Simulation results support the theory and illustrate the benefits of the spatio-temporal detector versus channel-by-channel detectors for low values of SNR.
36.	Ozcelikkale, Ayca, 1982, et al. (författare) Transmission Strategies for Remote Estimation under Energy Harvesting Constraints 2016 Ingår i: European Signal Processing Conference. - 2219-5491. - 9780992862657 ; , s. 572-576 Konferensbidrag (refereegranskat)abstract We consider the remote estimation of a time- correlated field using an energy harvesting (EH) sensor. The sensor observes the unknown field and communicates its observa- tions to a remote fusion center using an amplify-forward strategy. We consider the design of optimal transmission strategies in order to minimize the mean-square error (MSE) at the fusion center. Contrary to traditional approaches, the degree of correlation between the field values constitutes an important aspect of our formulation. We provide the optimal power allocation strategies for a number of illustrative scenarios, including the circularly wide-sense stationary (c.w.s.s.) signals with static correlation coefficient and the sampled low-pass c.w.s.s. signals. Based on these results, we propose low-complexity policies for the general case. Numerical evaluations illustrate the performance of the optimal and the low-complexity policies.
37.	Reinhold, Isabella, et al. (författare) Non-parametric Envelope Estimation for the Matched Window Reassignment 2021 Ingår i: 29th European Signal Processing Conference, EUSIPCO 2021 - Proceedings. - 2219-5491. - 9789082797060 ; 2021-August, s. 1920-1924 Konferensbidrag (refereegranskat)abstract The reassigned spectrogram is a powerful tool for analysing non-stationary signals, and in an ideal setting it gives perfect time and frequency localisation. A method very well suited for oscillating transient signals is the matched window reassignment, which requires a matching window, i.e. the envelope of the transient, to be known or estimated beforehand. This paper proposes a novel method for estimating the envelope of noisy transients, using a non-parametric and computationally efficient approach. The estimated envelopes are used to calculate the matched window reassignment, obtaining estimates of the time-frequency centre of the transients. The reassignment using the estimated envelopes is shown to give good estimates of the time-frequency centres, and good localisation in time and frequency. The novel envelope estimation approach is illustrated on measured marine biosonar data.
38.	Rudberg, Tore, et al. (författare) Robust Detection of Nuclear Quadrupole Resonance Signals in a Non-shielded Environment 2011 Ingår i: European Signal Processing Conference. - 2219-5491. ; 2011, s. 2079-2083 Konferensbidrag (refereegranskat)abstract Abstract in UndeterminedNuclear quadrupole resonance (NQR) is a non-invasiveradio-frequency technique allowing for a practically unique%ngerprint for molecules containing quadrupolar nuclei,making the technique very promising for detection purposes.If properly excited, these nuclei will emit electromagnetic radiation,the frequency of which is governed mainly by wherein the molecule the nuclei are positioned. However, the resultingNQR signals are inherently weak and are prone tostrong interference signals from the measurement environment,making detection challenging. In this paper, we developa robust and reliable detection algorithm that generalizeearlier techniques and incorporates both ef%cient interferencecancellation and the ability to handle multiple polymorphsin the sought substance. The usefulness of the algorithmis motivated by comparisons using realistic simulations.
39.	Saliu, Sokol, et al. (författare) Bispectral analysis of heart rate variability signal 2002 Ingår i: 11th European Signal Processing Conference, EUSIPCO 2002; Toulouse; France. - 2219-5491. ; 3, s. 407-410 Konferensbidrag (refereegranskat)
40.	Saliu, Sokol (författare) Definition of instantaneous frequency on real signals 2000 Ingår i: European Signal Processing Conference. - 2219-5491. ; 2015-March:March Konferensbidrag (refereegranskat)abstract This paper introduces a definition of the instantaneous frequency (IF) on real signals. Basically the definition ωt = xt/√1 - x2t avoids some pitfalls associated with the corresponding definition on analytic signals. It readily applies to the class of monocomponent frequency modulated signals and also accommodates the class of amplitude and frequency modulated signals. An interpretation of the IF is given for the latter and an extension of it to instantaneous parameters is discussed.
41.	Sandsten, Maria, et al. (författare) A Novel Multitaper Reassignment Method for Estimation of Phase Synchrony 2021 Ingår i: 29th European Signal Processing Conference, EUSIPCO 2021 - Proceedings. - 2219-5491. - 9789082797060 ; 2021-August, s. 2164-2168 Konferensbidrag (refereegranskat)abstract The matched phase reassignment, developed to estimate phase synchrony of transient oscillatory signals, is extended into a multitaper phase reassignment (MTPR) method. The method gives perfect time-frequency localization for two transients with zero phase difference and estimates of time locations and oscillatory frequencies in low signal-to-noise ratios. For different signal-to-noise ratios between channels a suggestion of corrected reassignment vector expressions is given, resulting in minimized variance. The MTPR outperforms the matched phase reassignment as well as state-of-the-art methods, such as Pearson's linear correlation, time-frequency cross-spectrogram phase estimation and the Phase Lag Index method. An example of estimated phase differences, time locations and oscillatory frequencies of electrical signals measured from the brain is also shown.
42.	Sandsten, Maria, et al. (författare) A SVD-based classification of bird singing in different time-frequency domains using multitapers 2011 Ingår i: European Signal Processing Conference. - 2219-5491. ; 2011, s. 966-970 Konferensbidrag (refereegranskat)abstract In this paper, a novel method for analysing a bird’s song is presented. The song of male great reed warblers is used for developing and testing the methods. A robust method for detecting syllables is proposed and a classification of those syllables as compared to reference syllables is done. The extraction of classification features are based on the use of singular vectors in different time-frequency domains, such as the ambiguity and the doppler domains, in addition to the usual sonogram. The analysis is also made using multitaper analysis where the Welch method and the Thomson multi- tapers are compared to the more recently proposed locally stationary process multitapers.
43.	Sandsten, Maria (författare) A Welch Method Approximation of the Thomson Multitaper Spectrum Estimator 2012 Ingår i: Signal Processing Conference (EUSIPCO), 2012 Proceedings of the 20th European. - 2219-5491. - 9781467310680 ; , s. 440-444 Konferensbidrag (refereegranskat)abstract The Thomson multitaper estimator has become successful for spectrum analysis in many application areas. From the aspect of efficient implementation, the so called Welch or WOSA- Weighted Overlap Segment Averaging, has advantages. In the Welch estimator, the same, time-shifted, window is applied to the data-sequence. In this submission, the aim is to find a Welch estimator structure which has a similar performance as the Thomson multitaper estimator. Such a estimator might be more advantageous from real-time computation aspects as the spectra can be estimated when data samples are available and a running average will produce the subsequent averaged spectra. The approach is to restructure the corresponding co- variance matrix of the Thomson estimator to the structure of a Welch estimator and to find a mean square error approxi- mation of the covariance matrix. The resulting window of the Welch estimator should however fulfill the usual properties of a spectrum estimator, such as low-pass structure and well suppressed sidelobes.
44.	Sandsten, Maria (författare) Multitaper Wigner distribution with pre-determined doppler-lag bandwdith and sidelobe suppression 2010 Ingår i: European Signal Processing Conference. - 2219-5491. ; 2010, s. 1737-1741 Konferensbidrag (refereegranskat)abstract Multi taper spectrogram decomposition of the time-lag kernel of a time-frequency distribution might result in computationally efficient calculations if the number of multi tapers to be considered in the spectrogram are small. In this paper, penalty functions are designed and used in the computation of multi tapers corresponding to the Wigner distribution time-lag kernel. The resulting multi taper spectrogram will approximately fulfill the concentration of the Wigner distribution but will also suppress the usual Wigner distribution cross-terms outside a predetermined doppler-lag bandwidth. The level of the cross-term suppression is determined by a parameter of the penalty function. The proposedmethod uses a limited number of multi tapers which is determined by the decided bandwidth. The time-frequency concentration of the proposed method is compared to other well-known distributions. The performance for white noise disturbances are also evaluated.
45.	Sandsten, Maria, et al. (författare) Parameter Estimation from the Cross-Spectrogram Reassignment Vectors 2021 Ingår i: 29th European Signal Processing Conference, EUSIPCO 2021 - Proceedings. - 2219-5491. - 9789082797060 ; 2021-August, s. 1915-1919 Konferensbidrag (refereegranskat)abstract In this paper we propose a novel technique to estimate the parameters of two Gaussian envelope oscillatory signals, with the same time-locations and oscillatory frequencies but possibly different phases. The phase difference and the length of the Gaussian envelope are estimated directly from the slopes of the corresponding cross-spectrogram reassignment vectors. Including the phase difference and the envelope length in the scaled reassignment of the cross-spectrogram will give a perfectly concentrated time-frequency spectrum where the location of the maximum gives estimates of the time and oscillatory frequency parameters. The proposed method is evaluated for different SNRs and is also compared to state-of-the-art techniques for phase estimation of oscillatory electrical activity measured from the brain.
46.	Savic, Vladimir, et al. (författare) Distributed target tracking based on belief propagation consensus 2012 Ingår i: European Signal Processing Conference. - 2219-5491. - 9781467310680 ; , s. 544-548, s. 544-548 Konferensbidrag (refereegranskat)abstract Distributed target tracking in wireless sensor networks (WSN) is an important problem, in which agreement on the target state can be achieved using particle filters with standard consensus methods, which may take long to converge. We propose distributed particle filtering based on belief propagation (DPF-BP) consensus, a fast method for target tracking. According to our simulations, DPF-BP provides better performance than DPF based on standard belief consensus (DPF-SBC) in terms of disagreement in the network. However, in terms of root-mean square error, it can outperform DPF-SBC only for a specific number of consensus iterations.
47.	Schlegel, Reent, 1994, et al. (författare) Straggler-Resilient Secure Aggregation for Federated Learning 2022 Ingår i: European Signal Processing Conference. - 2219-5491. ; 2022-August, s. 712-716 Konferensbidrag (refereegranskat)abstract We present CodedSecAgg, a straggler-resilient secure aggregation scheme for federated learning. CodedSecAgg introduces redundancy on the devices' data across the network, which is leveraged during the iterative learning phase at the central server to update the global model based on the responses of a subset of the devices. Compared to other schemes in the literature, which deal with device dropouts by ignoring the contribution of dropped devices, the proposed scheme does not suffer from the client-drift problem. We apply CodedSecAgg to a classification problem on the MNIST dataset. For a scenario with 120 devices, we show that CodedSecAgg outperforms state-of-the-art LightSecAgg in terms of latency by a factor of 6.6 to 15.8, depending on the number of colluding agents, for an accuracy of 95%.
48.	Simayijiang, Zhayida, et al. (författare) AN AUTOMATIC SYSTEM FOR MICROPHONE SELF-LOCALIZATION USING AMBIENT SOUND 2014 Ingår i: European Signal Processing Conference. - 2219-5491. Konferensbidrag (refereegranskat)abstract In this paper, we develop a system for microphone selflocalization based on ambient sound, without any assumptions on the 3D locations of the microphones and sound sources. We aim at developing a system capable of dealing with multiple moving sound sources. We will show that this is possible given that there are instances where there are only one dominating sound source. In the first step of the system we employ a feature detection and matching strategy. This produces TDOA data, possibly with missing data and with outliers. Then we use a robust and stratified approach for the parameter estimation. We use robust techniques to calculate initial estimates on the offsets parameters, followed by nonlinear optimization based on a rank criterion. Sequentially we use robust methods for calculating initial estimates of the sound source positions and microphone positions, followed by non-linear Maximum Likelihood estimation of all parameters. The methods are tested and verified using anechoic chamber sound recordings.
49.	Simayijiang, Zhayida, et al. (författare) MINIMAL SOLUTIONS FOR DUAL MICROPHONE RIG SELF-CALIBRATION 2014 Ingår i: European Signal Processing Conference. - 2219-5491. Konferensbidrag (refereegranskat)abstract In this paper, we study minimal problems related to dual microphone rig self-calibration using TOA measurements from sound sources with unknown positions. We consider the problems with varying setups as (i) if the internal distances between the microphone nodes are known a priori or not. (ii) if the microphone rigs lies in an affine space with different dimension than the sound sources. Solving these minimal problems is essential to robust estimation of microphone and sound source locations. We identify for each of these minimal problems the number of solutions in general and develop non-iterative solvers. We show that the proposed solvers are numerically stable in synthetic experiments. We also apply our method in a real indoor experiment and obtain accurate reconstruction using TOA measurements.
50.	Sjöberg, Jonas, 1964, et al. (författare) Driver models to increase the potential of automotive active safety functions 2010 Ingår i: Proceedings of 18th European Signal Processing Conference 2010, Aalborg, Denmark, August 23-27 2010. - 2219-5491. ; , s. 204-208 Konferensbidrag (refereegranskat)abstract This paper describes how the potential of some automotive active safety functions depend on the used driver model. It is shown that by including a more advanced driver model, it is possible to enhance the use of the signals from different sensor systems to let the active safety function intervene earlier and smoother so that the drivers are disturbed less, and the chance to avoid an accident increases.

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