J. Corr, K. Thompson, Stephan Weiss, I. Proudler, J. McWhirter
{"title":"Row-shift corrected truncation of paraunitary matrices for PEVD algorithms","authors":"J. Corr, K. Thompson, Stephan Weiss, I. Proudler, J. McWhirter","doi":"10.1109/EUSIPCO.2015.7362503","DOIUrl":"https://doi.org/10.1109/EUSIPCO.2015.7362503","url":null,"abstract":"In this paper, we show that the paraunitary (PU) matrices that arise from the polynomial eigenvalue decomposition (PEVD) of a parahermitian matrix are not unique. In particular, arbitrary shifts (delays) of polynomials in one row of a PU matrix yield another PU matrix that admits the same PEVD. To keep the order of such a PU matrix as low as possible, we propose a row-shift correction. Using the example of an iterative PEVD algorithm with previously proposed truncation of the PU matrix, we demonstrate that a considerable shortening of the PU order can be accomplished when using row-corrected truncation.","PeriodicalId":401040,"journal":{"name":"2015 23rd European Signal Processing Conference (EUSIPCO)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130892284","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Aleksandr Diment, Emre Çakir, T. Heittola, T. Virtanen
{"title":"Automatic recognition of environmental sound events using all-pole group delay features","authors":"Aleksandr Diment, Emre Çakir, T. Heittola, T. Virtanen","doi":"10.1109/EUSIPCO.2015.7362479","DOIUrl":"https://doi.org/10.1109/EUSIPCO.2015.7362479","url":null,"abstract":"A feature based on the group delay function from all-pole models (APGD) is proposed for environmental sound event recognition. The commonly used spectral features take into account merely the magnitude information, whereas the phase is overlooked due to the complications related to its interpretation. Additional information concealed in the phase is hypothesised to be beneficial for sound event recognition. The APGD is an approach to inferring phase information, which has shown applicability for speech and music analysis and is now studied in environmental audio. The evaluation is performed within a multi-label deep neural network (DNN) framework on a diverse real-life dataset of environmental sounds. It shows performance improvement compared to the baseline log mel-band energy case. Combined with the magnitude-based features, APGD demonstrates further improvement.","PeriodicalId":401040,"journal":{"name":"2015 23rd European Signal Processing Conference (EUSIPCO)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131301845","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
R. Grasso, P. Braca, S. Fortunati, F. Gini, M. Greco
{"title":"Environmental field estimation by consensus based dynamic sensor networks and underwater gliders","authors":"R. Grasso, P. Braca, S. Fortunati, F. Gini, M. Greco","doi":"10.1109/EUSIPCO.2015.7362374","DOIUrl":"https://doi.org/10.1109/EUSIPCO.2015.7362374","url":null,"abstract":"A coordinated dynamic sensor network of autonomous underwater gliders to estimate 3D time-varying environmental fields is proposed and tested. Each sensor performs local Kalman filter sequential field estimation. A network of surface relay nodes and asynchronous consensus are used to distribute local information among all nodes so that they can converge to an estimate of the global field. Tests using data from real oceanographic forecast models demonstrate the feasibility of the approach with relative error performance within 10%.","PeriodicalId":401040,"journal":{"name":"2015 23rd European Signal Processing Conference (EUSIPCO)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129255148","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Sparse signal recovery using a Bernoulli generalized Gaussian prior","authors":"Lotfi Chaari, J. Tourneret, C. Chaux","doi":"10.1109/EUSIPCO.2015.7362676","DOIUrl":"https://doi.org/10.1109/EUSIPCO.2015.7362676","url":null,"abstract":"Bayesian sparse signal recovery has been widely investigated during the last decade due to its ability to automatically estimate regularization parameters. Prior based on mixtures of Bernoulli and continuous distributions have recently been used in a number of recent works to model the target signals, often leading to complicated posteriors. Inference is therefore usually performed using Markov chain Monte Carlo algorithms. In this paper, a Bernoulli-generalized Gaussian distribution is used in a sparse Bayesian regularization framework to promote a two-level flexible sparsity. Since the resulting conditional posterior has anon-differentiable energy function, the inference is conducted using the recently proposed non-smooth Hamiltonian Monte Carlo algorithm. Promising results obtained with synthetic data show the efficiency of the proposed regularization scheme.","PeriodicalId":401040,"journal":{"name":"2015 23rd European Signal Processing Conference (EUSIPCO)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126859310","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Minimized roundoff noise and pole sensitivity subject to L2-Scaling constraints for IIR filters","authors":"Y. Hinamoto, A. Doi","doi":"10.1109/EUSIPCO.2015.7362558","DOIUrl":"https://doi.org/10.1109/EUSIPCO.2015.7362558","url":null,"abstract":"This paper investigates the minimization problem of weighted roundoff noise and pole sensitivity subject to l2-scaling constraints for state-space digital filters. A new measure for evaluating roundoff noise and pole sensitivity is proposed, and an efficient technique for minimizing this measure is developed. It is shown that the problem can be converted into an unconstrained optimization problem by using linear-algebraic techniques. The unconstrained optimization problem at hand is then solved iteratively by employing an efficient quasi-Newton algorithm with closed-form formulas for key gradient evaluation. Finally a numerical example is presented to demonstrate the validity and effectiveness of the proposed technique.","PeriodicalId":401040,"journal":{"name":"2015 23rd European Signal Processing Conference (EUSIPCO)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126860919","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Oversampled receive array calibration","authors":"Y. Abramovich, G. S. Antonio","doi":"10.1109/EUSIPCO.2015.7362439","DOIUrl":"https://doi.org/10.1109/EUSIPCO.2015.7362439","url":null,"abstract":"The problem of receive antenna array calibration in cases where the array is strongly spatially \"over-sampled\" is addressed in this paper. We suggest a new technique wherein spatially distributed strong clutter returns can be used for calibration with the goal of minimizing the power at the output of a number of antenna finger-beams steered into the invisible domain. The calibration algorithm is analyzed using simulation results and real over-the-horizon radar (OTHR) data to illustrate the effectiveness of the proposed technique.","PeriodicalId":401040,"journal":{"name":"2015 23rd European Signal Processing Conference (EUSIPCO)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123161815","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Wideband speech coding with hybrid digital-analog transmission","authors":"Matthias Rüngeler, Fabian Kleifgen, P. Vary","doi":"10.1109/EUSIPCO.2015.7362490","DOIUrl":"https://doi.org/10.1109/EUSIPCO.2015.7362490","url":null,"abstract":"Efficient digital transmission of speech requires source coding which comes at the price of unavoidable quantization errors. Thus, even in clear channel conditions, the quality of the decoded speech signal is limited due to the quantization errors. Hybrid Digital-Analog (HDA) codes circumvent this limitation by additionally transmitting the quantization error with quasi-analog methods (discrete-time, quasi-continuous-amplitude) with neither increasing the total transmission power, nor the occupied frequency bandwidth on the radio channel. So far, the HDA concept has mainly been applied to random parameters. In this paper, the HDA concept is adapted to the transmission of wideband speech signals using PCM and ADPCM coding. By experimental verification it is shown that the HDA concept may outperform conventional purely digital transmission systems at all channel qualities while additionally eliminating the quality saturation effect.","PeriodicalId":401040,"journal":{"name":"2015 23rd European Signal Processing Conference (EUSIPCO)","volume":"95 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123187770","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Managing trust in diffusion adaptive networks with malicious agents","authors":"K. Ntemos, N. Kalouptsidis, N. Kolokotronis","doi":"10.1109/EUSIPCO.2015.7362351","DOIUrl":"https://doi.org/10.1109/EUSIPCO.2015.7362351","url":null,"abstract":"In this paper, we consider the problem of information sharing over adaptive networks, where a diffusion strategy is used to estimate a common parameter. We introduce a new model that takes into account the presence of both selfish and malicious intelligent agents that adjust their behavior to maximize their own benefits. The interactions among agents are modeled as a stochastic game with incomplete information and partially observable actions. To stimulate cooperation amongst selfish agents and thwart malicious behavior, a trust management system relying on a voting scheme is employed. Agents act as independent learners, using the Q-learning algorithm. The simulation results illustrate the severe impact of falsified information on estimation accuracy along with the noticeable improvements gained by stimulating cooperation and truth-telling, with the proposed trust management mechanism.","PeriodicalId":401040,"journal":{"name":"2015 23rd European Signal Processing Conference (EUSIPCO)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126295891","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Distributed acoustic slam","authors":"Lukasz Grzymkowski, K. Glowczewski, S. Raczynski","doi":"10.1109/EUSIPCO.2015.7362647","DOIUrl":"https://doi.org/10.1109/EUSIPCO.2015.7362647","url":null,"abstract":"Vision-based methods are very popular for simultaneous localization and environment mapping (SLAM). One can imagine that exploiting the natural acoustic landscape of the robot's environment can prove to be a useful alternative to vision SLAM. Visual SLAM depends on matching local features between images, whereas distributed acoustic SLAM is based on matching acoustic events. Proposed DASLAM is based on distributed microphone arrays, where each microphone is connected to a separate, moving, controllable recording device, which requires compensation for their different clock shifts. We show that this controlled mobility is necessary to deal with underdetermined cases. Estimation is done using particle filtering. Results show that both tasks can be accomplished with good precision, even for the theoretically underdetermined cases. For example, we were able to achieve mapping error as low as 17.53 cm for sound sources with localization error of 18.61 cm and clock synchronization error of 42 μs for 2 robots and 2 sources.","PeriodicalId":401040,"journal":{"name":"2015 23rd European Signal Processing Conference (EUSIPCO)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122328692","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Classification of normal and pathological infant cries using bispectrum features","authors":"Anshu Chittora, H. Patil","doi":"10.1109/EUSIPCO.2015.7362461","DOIUrl":"https://doi.org/10.1109/EUSIPCO.2015.7362461","url":null,"abstract":"In this paper, bispectrum-based feature extraction method is proposed for classification of normal vs. pathological infant cries. Bispectrum is computed for all segments of normal as well as pathological cries. Bispectrum is a two-dimensional (2-D) feature. A tensor is formed using these bispectrum features and then for feature reduction, higher order singular value decomposition theorem (HOSVD) is applied. Our experimental results show 70.56 % average accuracy of classification with support vector machine (SVM) classifier, whereas baseline features, viz., MFCC, LPC and PLP gave classification accuracy of 52.41 %, 61.27 % and 57.41 %, respectively. For showing the effectiveness of the proposed feature extraction method, a comparison with other feature extraction methods which uses diagonal slice and peaks and their locations as feature vectors is given as well.","PeriodicalId":401040,"journal":{"name":"2015 23rd European Signal Processing Conference (EUSIPCO)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115246910","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}