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Enumeration	Reference	Cover	Find
1.	Angelopoulos, Kostas, et al. (author) Efficient Time Recursive Coherence Spectrum Estimation 2012 In: Signal Processing Conference (EUSIPCO), 2012 Proceedings of the 20th European. - 2076-1465 .- 2219-5491. - 9781467310680 ; , s. 425-429 Conference paper (peer-reviewed)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.
2.	Jensen, Jesper, et al. (author) Computationally Efficient IAA-Based Estimation of the Fundamental Frequency 2012 In: Signal Processing Conference (EUSIPCO), 2012 Proceedings of the 20th European. - 2076-1465 .- 2219-5491. - 9781467310680 ; , s. 2163-2167 Conference paper (peer-reviewed)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.
3.	Soldi, Giovanni, et al. (author) Wireless Positioning using Ellipsoidal Constraints 2012 In: Signal Processing Conference (EUSIPCO), 2012 Proceedings of the 20th European. - 2219-5491 .- 2076-1465. - 9781467310680 ; , s. 190-194 Conference paper (peer-reviewed)abstract Indoor location-based positioning systems have attracted notable interest during recent years for a wide range of personal and commercial applications. As is well known, the GPS systems does not allow for accurate positioning indoors, resulting in the development of various forms of indoor positioning techniques, mostly being based on radio frequency measurements. In this paper, we examine a novel way to reduce the positioning error by using the notion of separating ellipsoids in the context of received signal strength (RSS) fingerprinting. To avoid excessive computational complexity, the algorithmis paired with the A* algorithm, exploiting mapping information of the building of interest, to take into account obstacles such as walls. The proposed algorithm is evaluated on RSS measurements made in a shopping mall, and found to offer an improved positioning accuracy as compared to the Gaussian kernel approach.
4.	Aström, Kalle, et al. (author) Extension of Time-Difference-of-Arrival Self Calibration Solutions Using Robust Multilateration 2021 In: 29th European Signal Processing Conference, EUSIPCO 2021 - Proceedings. - 2076-1465 .- 2219-5491. - 9789082797060 ; , s. 870-874 Conference paper (peer-reviewed)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.
5.	Sandsten, Maria (author) A Welch Method Approximation of the Thomson Multitaper Spectrum Estimator 2012 In: Signal Processing Conference (EUSIPCO), 2012 Proceedings of the 20th European. - 2219-5491. - 9781467310680 ; , s. 440-444 Conference paper (peer-reviewed)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.
6.	Savic, Vladimir, et al. (author) Distributed target tracking based on belief propagation consensus 2012 In: European Signal Processing Conference. - 2219-5491. - 9781467310680 ; , s. 544-548, s. 544-548 Conference paper (peer-reviewed)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.
7.	Glentis, G. -O, et al. (author) Efficient spectral analysis in the missing data case using sparse ML methods 2014 In: European Signal Processing Conference. - 2219-5491. Conference paper (peer-reviewed)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.
8.	Adalbjörnsson, Stefan Ingi, et al. (author) High resolution sparse estimation of exponentially decaying two-dimensional signals 2014 In: European Signal Processing Conference. - 2219-5491. Conference paper (peer-reviewed)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.
9.	Adalbjörnsson, Stefan Ingi, et al. (author) Sparse Estimation Of Spectroscopic Signals 2011 In: European Signal Processing Conference. - 2219-5491. ; 2011, s. 333-337 Conference paper (peer-reviewed)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.
10.	Akesson, Maria, et al. (author) Highly Accurate and Noise-Robust Phase Delay Estimation using Multitaper Reassignment 2023 In: 31st European Signal Processing Conference, EUSIPCO 2023 - Proceedings. - 2219-5491. - 9789464593600 ; , s. 1763-1767 Conference paper (peer-reviewed)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.
11.	Akesson, Maria, et al. (author) Phase Reassignment with Efficient Estimation of Phase Difference 2022 In: 30th European Signal Processing Conference, EUSIPCO 2022 - Proceedings. - 2219-5491. - 9789082797091 ; 2022-August, s. 2126-2130 Conference paper (peer-reviewed)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.
12.	Ambat, Sooraj K., et al. (author) Fusion of greedy pursuits for compressed sensing signal reconstruction 2012 In: 2012 Proceedings Of The 20th European Signal Processing Conference (EUSIPCO). - : IEEE Computer Society. - 9781467310680 ; , s. 1434-1438 Conference paper (peer-reviewed)abstract Greedy Pursuits are very popular in Compressed Sensing for sparse signal recovery. Though many of the Greedy Pursuits possess elegant theoretical guarantees for performance, it is well known that their performance depends on the statistical distribution of the non-zero elements in the sparse signal. Inpractice, the distribution of the sparse signal may not be knowna priori. It is also observed that performance of Greedy Pursuits degrades as the number of available measurements decreases from a threshold value which is method dependent. To improve the performance in these situations, we introduce a novel fusion framework for Greedy Pursuits and also propose two algorithms for sparse recovery. Through Monte Carlo simulations we show that the proposed schemes improve sparse signal recovery in clean as well as noisy measurement cases.
13.	Andersson, Matilda, et al. (author) Augmentation Strategies for Self-Supervised Representation Learning from Electrocardiograms 2023 In: 31st European Signal Processing Conference, EUSIPCO 2023 - Proceedings. - 2219-5491. - 9789464593600 ; , s. 1075-1079 Conference paper (peer-reviewed)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.
14.	Ask, Erik, et al. (author) A Unifying Approach to Minimal Problems in Collinear and Planar TDOA Sensor Network Self-Calibration 2014 In: European Signal Processing Conference. - 2219-5491. Conference paper (peer-reviewed)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.
15.	Babu, Prabhu, et al. (author) Sparse spectral-line estimation for nonuniformly sampled multivariate time series : SPICE, LIKES and MSBL 2012 In: 2012 Proceedings Of The 20th European Signal Processing Conference (EUSIPCO). - 9781467310680 ; , s. 445-449 Conference paper (peer-reviewed)abstract In this paper we deal with the problem of spectral-line analysis ofnonuniformly sampled multivariate time series for which we introduce two methods: the ﬁrst method named SPICE (sparse iterativecovariance based estimation) is based on a covariance ﬁtting framework whereas the second method named LIKES (likelihood-basedestimation of sparse parameters) is a maximum likelihood technique. Both methods yield sparse spectral estimates and they donot require the choice of any hyperparameters. We numericallycompare the performance of SPICE and LIKES with that of the recently introduced method of multivariate sparse Bayesian learning(MSBL).
16.	Björk, Marcus, 1985-, et al. (author) Signal Processing Algorithms for Removing Banding Artifacts in MRI 2011 In: Proceedings of the 19th European Signal Processing Conference (EUSIPCO-2011). ; , s. 1000-1004, s. 1000-1004 Conference paper (peer-reviewed)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.
17.	Björnson, Emil, et al. (author) DISTRIBUTED MASSIVE MIMO IN CELLULAR NETWORKS: IMPACT OF IMPERFECT HARDWARE AND NUMBER OF OSCILLATORS 2015 In: 2015 23rd European Signal Processing Conference. - : Institute of Electrical and Electronics Engineers (IEEE). - 2076-1465. - 9780992862633 ; , s. 2436-2440 Conference paper (peer-reviewed)abstract Distributed massive multiple-input multiple-output (MIMO) combines the array gain of coherent MIMO processing with the proximity gains of distributed antenna setups. In this paper, we analyze how transceiver hardware impairments affect the downlink with maximum ratio transmission. We derive closed-form spectral efficiencies expressions and study their asymptotic behavior as the number of the antennas increases. We prove a scaling law on the hardware quality, which reveals that massive MIMO is resilient to additive distortions, while multiplicative phase noise is a limiting factor. It is also better to have separate oscillators at each antenna than one per BS.
18.	Brynolfsson, Johan, et al. (author) Multitaper Estimation of the Coherence Spectrum in low SNR 2014 In: European Signal Processing Conference. - 2219-5491. Conference paper (peer-reviewed)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.
19.	Cipriano, Antonio, et al. (author) Cooperative Communications with HARQ in a Wireless Mesh Network Based on 3GPP LTE 2012 In: Signal Processing Conference (EUSIPCO), 2012. - : IEEE. - 9781467310680 ; , s. 1004-1008 Conference paper (peer-reviewed)abstract This paper presents some results from of the FP7 ICT-LOLA (achieving LOw LAtency in wireless communications) project on the design of clusterized wireless mesh network based on 3GPP LTE. First, we focus on the general MAC/PHY structure of the clusterized mesh network based on 3GPP LTE. Then, the concept of virtual link is presented for inter-cluster communications combining MAC layer forwarding, hybrid automatic repeat request (HARQ) and cooperative communications with Decode and Forward (DF). The goal of a virtual link is to enable low latency data transfer in inter-cluster communications. The virtual link solution is studied by simulations thanks to OpenAirInterface which integrates LTE MAC and PHY layer procedures, as well as adaptations needed for the LOLA wireless mesh network. Simulation results show that the proposed distributed solution smoothly adapts to the link conditions. A loss in throughput efficiency is the price to be paid in certain configurations for the distributed operation of the virtual link. Nevertheless, the technique helps in reducing the average number of transmissions thus contributing to improve the latency of the system.
20.	Dai, Liang, et al. (author) An ellipsoid based, two-stage screening test for BPDN 2012 In: Proc. 20th European Signal Processing Conference. - : IEEE. - 9781467310680 ; , s. 654-658 Conference paper (peer-reviewed)
21.	Elvander, Filip, et al. (author) Robust Non-Negative Least Squares Using Sparsity 2016 In: 2016 24th European Signal Processing Conference (EUSIPCO). - 2076-1465. - 9780992862657 ; , s. 61-65 Conference paper (peer-reviewed)abstract Sparse, non-negative signals occur in many applications. To recover such signals, estimation posed as non-negative least squares problems have proven to be fruitful. Efficient algorithms with high accuracy have been proposed, but many of them assume either perfect knowledge of the dictionary generating the signal, or attempts to explain deviations from this dictionary by attributing them to components that for some reason is missing from the dictionary. In this work, we propose a robust non-negative least squares algorithm that allows the generating dictionary to differ from the assumed dictionary, introducing uncertainty in the setup. The proposed algorithm enables an improved modeling of the measurements, and may be efficiently implemented using a proposed ADMM implementation. Numerical examples illustrate the improved performance as compared to the standard non-negative LASSO estimator.
22.	Faundez-Zanuy, M., et al. (author) On the relevance of bandwidth extension for speaker identification 2015 In: European Signal Processing Conference. - : EUSIPCO. - 2219-5491. Journal article (peer-reviewed)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.
23.	Fernandez, Joel, et al. (author) Linearization of Active Array Transmitters Under Crosstalk via Over-the-Air Observations 2023 In: European Signal Processing Conference. - 2219-5491. ; , s. 1420-1424 Conference paper (peer-reviewed)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.
24.	Ferranti, Luca, et al. (author) Homotopy Continuation for Sensor Networks Self-Calibration 2021 In: 29th European Signal Processing Conference, EUSIPCO 2021 - Proceedings. - 2219-5491. - 9789082797060 ; 2021-August, s. 1725-1729 Conference paper (peer-reviewed)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.
25.	Ferreol, A., et al. (author) A New Expression of the Asymptotic Performances of Maximum Likelihood DOA Estimation Method With Modeling Errors 2004 In: Proceeding EURASIP 2004, Vienna, Austria.. - 2219-5491. - 9783200001657 ; 06-10-September-2004, s. 2163-2166 Conference paper (peer-reviewed)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.
26.	Ferreol, A., et al. (author) Modeling error sensitivity of the MUSIC algorithm conditioned on resolved sources 2008 In: European Signal Processing Conference. - 2219-5491. Conference paper (peer-reviewed)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.
27.	Garcia, Guillermo, 1976, et al. (author) A Methodology for speaker-dependent acoustic features based on a simplified cortical response for speaker verification systems 2009 In: 17th European Signal Processing Conference, EUSIPCO 2009; Glasgow; United Kingdom; 24 August 2009 through 28 August 2009. - 2219-5491. ; , s. 1240-1243 Conference paper (peer-reviewed)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.
28.	Garcia, Guillermo, 1976, et al. (author) Sample iterative likelihood maximization for speaker verification systems 2010 In: 18th European Signal Processing Conference, EUSIPCO 2010; Aalborg; Denmark; 23 August 2010 through 27 August 2010. - 2219-5491. ; , s. 596-600 Conference paper (peer-reviewed)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.
29.	Garcia, Guillermo, 1976, et al. (author) Study of mutual information for speaker recognition features 2010 In: 18th European Signal Processing Conference, EUSIPCO 2010; Aalborg; Denmark; 23 August 2010 through 27 August 2010. - 2219-5491. ; , s. 601-605 Conference paper (peer-reviewed)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.
30.	Glentis, George-Othan, et al. (author) Preconditioned Conjugate Gradient IAA Spectral Estimation 2011 In: European Signal Processing Conference. - 2219-5491. ; 2001, s. 1195-1199 Conference paper (peer-reviewed)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.
31.	Hiltunen, Sonja, et al. (author) Comparison of two proximal splitting algorithms for solving multilabel disparity estimation problems 2012 In: 2012 Proceedings Of The 20th European Signal Processing Conference (EUSIPCO). - : IEEE Computer Society. - 9781467310680 ; , s. 1134-1138 Conference paper (peer-reviewed)abstract Disparity estimation constitutes an active research area in stereo vision, and in recent years, global estimation methods aiming at minimizing an energy function over the whole image have gained a lot of attention. To overcome the difficulties raised by the nonconvexity of the minimized criterion, convex relaxations have been proposed by several authors. In this paper, the global energy function is made convex by quantizing the disparity map and converting it into a set of binary fields. It is shown that the problem can then be efficiently solved by parallel proximal splitting approaches. A primal algorithm and a primal-dual one are proposed and compared based on numerical tests.
32.	Hongmei, Hu, et al. (author) Sparsity level in a non-negative matrix factorization based speech strategy in cochlear implants 2012 In: 2012 Proceedings Of The 20th European Signal Processing Conference (EUSIPCO). - : IEEE Computer Society. - 9781467310680 ; , s. 2432-2436 Conference paper (peer-reviewed)abstract Non-negative matrix factorization (NMF) has increasinglybeen used as a tool in signal processing in the last years, butit has not been used in the cochlear implants (CIs). Toimprove the performance of CIs in noisy environments, anovel sparse strategy is proposed by applying NMF onenvelops of 22 channels. In the new algorithm, the noisyspeech is first transferred to the time-frequency domain viaa 22- channel filter bank and the envelope in each frequencychannel is extracted; secondly, NMF is applied to theenvelope matrix (envelopegram); finally, the sparsitycondition is applied to the coefficient matrix to get moresparse representation. Speech reception threshold (SRT)subjective experiment was performed in combination withfive objective measurements in order to choose the properparameters for the sparse NMF model.
33.	Jansson, Andreas, et al. (author) Range-based radar model structure selection 2021 In: 28th European Signal Processing Conference, EUSIPCO 2020 - Proceedings. - 2219-5491. - 9789082797053 ; 2021-January, s. 2269-2273 Conference paper (peer-reviewed)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.
34.	Johansson, Håkan, et al. (author) A realization of FIR filters with simultaneously variable bandwidth and fractional delay 2012 In: Signal Processing Conference (EUSIPCO), 2012. - : IEEE. - 9781467310680 ; , s. 2178-2182 Conference paper (peer-reviewed)abstract This paper introduces a realization of finite-length impulse response (FIR) filters with simultaneously variable bandwidth and fractional delay (FD). The realization makes use of impulse responses which are two-dimensional polynomials in the bandwidth and FD parameters. Unlike previous polynomial-based realizations, it utilizes the fact that a variable FD filter is typically much less complex than a variable-bandwidth filter. By separating the corresponding subfilters in the overall realization, significant savings are thereby achieved. A design example, included in the paper, shows about 65 percent multiplication and addition savings compared to the previous polynomial-based realizations. Moreover, compared to a recently introduced alternative fast filter bank approach, the proposed method offers significantly smaller group delays and group delay errors.
35.	Juhlin, Maria, et al. (author) Localization Of Multiple Jammers In Wireless Sensor Networks 2021 In: 29th European Signal Processing Conference, EUSIPCO 2021 - Proceedings. - 2219-5491. - 9789082797060 ; 2021-August, s. 1596-1600 Conference paper (peer-reviewed)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.
36.	Juhlin, Maria, et al. (author) Optimal microphone placement for localizing tonal sound sources 2021 In: 28th European Signal Processing Conference, EUSIPCO 2020 - Proceedings. - 2219-5491. - 9789082797053 ; 2021-January, s. 236-240 Conference paper (peer-reviewed)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.
37.	Katselis, Dimitrios, et al. (author) On OFDM/OQAM receivers 2012 In: 2012 Proceedings Of The 20th European Signal Processing Conference (EUSIPCO). - : IEEE Computer Society. - 9781467310680 ; , s. 2566-2570 Conference paper (peer-reviewed)abstract In OFDM/OQAM systems, the presence of the intrinsic interference effect, caused by the lack of complex field orthogonality of the pulses employed, challenges the symbol detection task at the receiver. In this paper, the problem of equalization in such a system is studied, through the comparative analysis of three approaches to zero forcing equalization: (a) the classical receiver, which operates directly on the received signal at each subcarrier without any additional processing, (b) the dispersive receiver, forming sufficient statistics for the symbol decision, and (c) an alternative approach, which aims at completely eliminating intrinsic interference before deciding the symbols. The receivers are formulated and analyzed under the common assumptions for the OFDM/OQAM input/output model. The classical receiver is then shown to perform similarly with the other two for relatively short channels, while it outperforms them when the channel dispersion is large with respect to the number of subcarriers. Through these results, the sensitivity of the detection performance of alternative receivers to the validity of the input/output model is revealed and assessed.
38.	Keding, Oskar, et al. (author) Coherence Expectation Minimisation and Combining Weighted Multitaper Estimates 2023 In: 31st European Signal Processing Conference, EUSIPCO 2023 - Proceedings. - 2219-5491. - 9789464593600 ; , s. 1993-1997 Conference paper (peer-reviewed)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.
39.	Keding, Oskar, et al. (author) ROBUST PHASE DIFFERENCE ESTIMATION OF TRANSIENTS IN HIGH NOISE LEVELS 2022 In: 30th European Signal Processing Conference, EUSIPCO 2022 - Proceedings. - 2219-5491. - 9789082797091 ; 2022-August, s. 2271-2275 Conference paper (peer-reviewed)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.
40.	Klang, Göran, et al. (author) Interference Rejection in Systems Employing Transmit Diversity 2002 In: European Signal Processing Conference. - : EUSIPCO. - 2219-5491. Journal article (peer-reviewed)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.
41.	Kronvall, Ted, et al. (author) An Adaptive Penalty Approach to Multi-Pitch Estimation 2015 In: Signal Processing Conference (EUSIPCO), 2015 23rd European. - 2076-1465. - 9780992862633 Conference paper (peer-reviewed)abstract This work treats multi-pitch estimation, and in particular the common misclassification issue wherein the pitch at half of the true fundamental frequency, here referred to as a sub-octave, is chosen instead of the true pitch. Extending on current methods which use an extension of the Group LASSO for pitch estimation, this work introduces an adaptive total variation penalty, which both enforce group- and block sparsity, and deal with errors due to sub-octaves. The method is shown to outperform current state-of-the-art sparse methods, where the model orders are unknown, while also requiring fewer tuning parameters than these. The method is also shown to outperform several conventional pitch estimation methods, even when these are virtued with oracle model orders.
42.	Kronvall, Ted, et al. (author) Joint DOA and Multi-Pitch Estimation Via Block Sparse Dictionary Learning 2014 In: European Signal Processing Conference. - 2219-5491. Conference paper (peer-reviewed)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.
43.	Kronvall, Ted, et al. (author) Multi-pitch estimation via fast group sparse learning 2016 In: 2016 24th European Signal Processing Conference (EUSIPCO). - 2076-1465. - 9780992862657 ; , s. 1093-1097 Conference paper (peer-reviewed)abstract In this work, we consider the problem of multi-pitch estimation using sparse heuristics and convex modeling. In general, this is a difficult non-linear optimization problem, as the frequencies belonging to one pitch often overlap the frequencies belonging to other pitches, thereby causing ambiguity between pitches with similar frequency content. The problem is further complicated by the fact that the number of pitches is typically not known. In this work, we propose a sparse modeling framework using a generalized chroma representation in order to remove redundancy and lower the dictionary's block-coherency. The found chroma estimates are then used to solve a small convex problem, whereby spectral smoothness is enforced, resulting in the corresponding pitch estimates. Compared with previously published sparse approaches, the resulting algorithm reduces the computational complexity of each iteration, as well as speeding up the overall convergence.
44.	Kronvall, Ted, et al. (author) Online Group-Sparse Regression Using the Covariance Fitting Criterion 2017 In: Proceedings of the 25th European Signal Processing Conference (EUSIPCO). - 2076-1465. - 9780992862688 ; CFP1740S-USB Conference paper (peer-reviewed)abstract In this paper, we present a time-recursive implementation of a recent hyperparameter-free group-sparse estimation technique. This is achieved byr eformulating the original method, termed group-SPICE, as a square-root group-LASSO with a suitable regularization level, for which a time-recursive implementation is derived. Using a proximal gradient step for lowering the computational cost, the proposed method may effectively cope with data sequences consisting of both stationary and non-stationary signals, such as transients, and/or amplitude modulated signals. Numerical examples illustrates the efﬁcacy of the proposed method for both coherent Gaussian dictionaries and for the multi-pitch estimation problem.
45.	Kyriakidou, Georgia, et al. (author) Improved modeling and bounds for NQR spectroscopy signals 2014 In: European Signal Processing Conference. - 2219-5491. Conference paper (peer-reviewed)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.
46.	Larsson, Malte, et al. (author) Efficient Time-of-Arrival Self-Calibration using Source Implicitization 2023 In: 31st European Signal Processing Conference, EUSIPCO 2023 - Proceedings. - 2219-5491. - 9789464593600 ; , s. 1644-1648 Conference paper (peer-reviewed)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.
47.	Ma, Zhanyu (author) Bayesian estimation of the Dirichlet distribution with expectation propagation 2012 In: Signal Processing Conference (EUSIPCO), 2012 Proceedings of the 20th European. - : IEEE Computer Society. - 9781467310680 ; , s. 689-693 Conference paper (peer-reviewed)abstract As a member of the exponential family, the Dirichlet distribution has its conjugate prior. However, since the posterior distribution is difficult to use in practical problems, Bayesian estimation of the Dirichlet distribution, in general, is not analytically tractable. To derive practically easily used prior and posterior distributions, some approximations are required to approximate both the prior and the posterior distributions so that the conjugate match between the prior and posterior distributions holds and the obtained posterior distribution is easy to be employed. To this end, we approximate the distribution of the parameters in the Dirichlet distribution by a multivariate Gaussian distribution, based on the expectation propagation (EP) framework. The EP-based method captures the correlations among the parameters and provides an easily used prior/posterior distribution. Compared to recently proposed Bayesian estimation based on the variation inference (VI) framework, the EP-based method performs better with a smaller amount of observed data and is more stable.
48.	McKelvey, Tomas, 1966 (author) Auto-calibration of Uniform Linear Array Antennas 2019 In: European Signal Processing Conference. - 2219-5491. ; 2019-September Conference paper (peer-reviewed)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.
49.	Miri, Maliheh, et al. (author) Brain fingerprinting using EEG graph inference 2023 In: 31st European Signal Processing Conference, EUSIPCO 2023 - Proceedings. - 2219-5491. - 9789464593600 ; , s. 1025-1029 Conference paper (peer-reviewed)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.
50.	Månsson, Anders, et al. (author) Multidimensional Cramér-Rao Lower Bound for Non-uniformly Sampled NMR Signals 2014 In: European Signal Processing Conference. - 2219-5491. Conference paper (peer-reviewed)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.

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