In this paper, we present a new method for increasing the number of resolvable sources in direction-of-arrival estimation using co-prime arrays. This is achieved by utilizing multiple frequencies to fill in the missing elements in the difference coarray of the co-prime array corresponding to the reference frequency. For high signal-to-noise ratio, the multi-frequency approach effectively utilizes all of the degrees-of-freedom offered by the coarray, provided that the sources have proportional spectra. The performance of the proposed method is evaluated through numerical simulations.
{"title":"Direction-of-arrival estimation using multi-frequency co-prime arrays","authors":"Elie BouDaher, Yong Jia, F. Ahmad, M. Amin","doi":"10.5281/ZENODO.43952","DOIUrl":"https://doi.org/10.5281/ZENODO.43952","url":null,"abstract":"In this paper, we present a new method for increasing the number of resolvable sources in direction-of-arrival estimation using co-prime arrays. This is achieved by utilizing multiple frequencies to fill in the missing elements in the difference coarray of the co-prime array corresponding to the reference frequency. For high signal-to-noise ratio, the multi-frequency approach effectively utilizes all of the degrees-of-freedom offered by the coarray, provided that the sources have proportional spectra. The performance of the proposed method is evaluated through numerical simulations.","PeriodicalId":198408,"journal":{"name":"2014 22nd European Signal Processing Conference (EUSIPCO)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116985530","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}
In a previous work [1], we have shown that model interpolation can be applied for acoustic model adaptation for a specific show. Compared to other approaches, this method has the advantage to be highly flexible, allowing rapid adaptation by simply reassigning the interpolation coefficients. In this work this approach is used for a multi-accented English broadcast news data recognition, which can be considered an arduous task due to the impact of accent variability on the recognition performance. The work described in [1] is extended in two ways. First, in order to reduce the parameters of the interpolated model, a theoretically motivated EM-like mixture reduction algorithm is proposed. Second, beyond supervised adaptation, model interpolation is used as an unsupervised adaptation framework, where the interpolation coefficients are estimated on-the-fly for each test segment.
{"title":"Speech recognition of multiple accented English data using acoustic model interpolation","authors":"Thiago Fraga-Silva, J. Gauvain, L. Lamel","doi":"10.5281/ZENODO.44197","DOIUrl":"https://doi.org/10.5281/ZENODO.44197","url":null,"abstract":"In a previous work [1], we have shown that model interpolation can be applied for acoustic model adaptation for a specific show. Compared to other approaches, this method has the advantage to be highly flexible, allowing rapid adaptation by simply reassigning the interpolation coefficients. In this work this approach is used for a multi-accented English broadcast news data recognition, which can be considered an arduous task due to the impact of accent variability on the recognition performance. The work described in [1] is extended in two ways. First, in order to reduce the parameters of the interpolated model, a theoretically motivated EM-like mixture reduction algorithm is proposed. Second, beyond supervised adaptation, model interpolation is used as an unsupervised adaptation framework, where the interpolation coefficients are estimated on-the-fly for each test segment.","PeriodicalId":198408,"journal":{"name":"2014 22nd European Signal Processing Conference (EUSIPCO)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117101652","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}
In this paper, we examine the descriptiveness and recognition properties of different feature representations for the analysis of musical signals, aiming in the exploration of their microand macro-structures, for the task of music genre classification. We explore nonlinear methods, such as the AM-FM model and ideas from fractal theory, so as to model the time-varying harmonic structure of musical signals and the geometrical complexity of the music waveform. The different feature representations' efficacy is compared regarding their recognition properties for the specific task. The proposed features are evaluated against and in combination with Mel frequency cepstral coefficients (MFCC), using both static and dynamic classifiers, accomplishing an error reduction of 28%, illustrating that they can capture important aspects of music.
{"title":"Comparison of different representations based on nonlinear features for music genre classification","authors":"Athanasia Zlatintsi, P. Maragos","doi":"10.5281/ZENODO.44161","DOIUrl":"https://doi.org/10.5281/ZENODO.44161","url":null,"abstract":"In this paper, we examine the descriptiveness and recognition properties of different feature representations for the analysis of musical signals, aiming in the exploration of their microand macro-structures, for the task of music genre classification. We explore nonlinear methods, such as the AM-FM model and ideas from fractal theory, so as to model the time-varying harmonic structure of musical signals and the geometrical complexity of the music waveform. The different feature representations' efficacy is compared regarding their recognition properties for the specific task. The proposed features are evaluated against and in combination with Mel frequency cepstral coefficients (MFCC), using both static and dynamic classifiers, accomplishing an error reduction of 28%, illustrating that they can capture important aspects of music.","PeriodicalId":198408,"journal":{"name":"2014 22nd European Signal Processing Conference (EUSIPCO)","volume":"137 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123289086","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}
This paper presents a novel approach for room reconstruction using unknown sound signals generated in different locations of the environment. The approach is very general, that is fully uncalibrated, i.e. the locations of microphones, sound events and room reflectors are not known a priori. We show that, even if this problem implies a highly non-linear cost function, it is still possible to provide a solution close to the global minimum. Synthetic experiments show the proposed optimization framework can achieve reasonable results even in the presence of signal noise.
{"title":"Towards fully uncalibrated room reconstruction with sound","authors":"M. Crocco, A. Trucco, Vittorio Murino, A. D. Bue","doi":"10.5281/ZENODO.43892","DOIUrl":"https://doi.org/10.5281/ZENODO.43892","url":null,"abstract":"This paper presents a novel approach for room reconstruction using unknown sound signals generated in different locations of the environment. The approach is very general, that is fully uncalibrated, i.e. the locations of microphones, sound events and room reflectors are not known a priori. We show that, even if this problem implies a highly non-linear cost function, it is still possible to provide a solution close to the global minimum. Synthetic experiments show the proposed optimization framework can achieve reasonable results even in the presence of signal noise.","PeriodicalId":198408,"journal":{"name":"2014 22nd European Signal Processing Conference (EUSIPCO)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124771186","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}
In this work, we propose a cross-layer design strategy based on a joint successive interference cancellation (SIC) detection technique and a multi-relay selection algorithm for the uplink of cooperative direct-sequence code-division multiple access (DS-CDMA) systems. We devise a low-cost greedy list-based SIC (GL-SIC) strategy with RAKE receivers as the front-end that can approach the maximum likelihood detector performance. We also present a low-complexity multi-relay selection algorithm based on greedy techniques that can approach the performance of an exhaustive search. Simulations show an excellent bit error rate performance of the proposed detection and relay selection algorithms as compared to existing techniques.
{"title":"Joint sic and multi-relay selection algorithms for cooperative DS-CDMA systems","authors":"Jiaqi Gu, R. D. Lamare","doi":"10.5281/ZENODO.43825","DOIUrl":"https://doi.org/10.5281/ZENODO.43825","url":null,"abstract":"In this work, we propose a cross-layer design strategy based on a joint successive interference cancellation (SIC) detection technique and a multi-relay selection algorithm for the uplink of cooperative direct-sequence code-division multiple access (DS-CDMA) systems. We devise a low-cost greedy list-based SIC (GL-SIC) strategy with RAKE receivers as the front-end that can approach the maximum likelihood detector performance. We also present a low-complexity multi-relay selection algorithm based on greedy techniques that can approach the performance of an exhaustive search. Simulations show an excellent bit error rate performance of the proposed detection and relay selection algorithms as compared to existing techniques.","PeriodicalId":198408,"journal":{"name":"2014 22nd European Signal Processing Conference (EUSIPCO)","volume":"2010 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125985433","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}
In the field of underlay cognitive radio communications, the signal transmitted by the secondary user is disturbed by incoming signals from primary users. Thus, it is necessary to compensate for this secondary-link degradation at the receiver level. In this paper we use Dirichlet process mixtures (DPM) to relax a priori assumptions on the characteristics of the primary user-induced interference. DPM allow us to model the probability density function of the interference. The latter is estimated jointly with the symbols and the channel of the secondary link by using marginalized particle filtering. Our approach makes it possible to improve the symbol error rate compared with an algorithm that simply models the interference as a Gaussian noise.
{"title":"Relevance of Dirichlet process mixtures for modeling interferences in underlay cognitive radio","authors":"V. Pereira, G. Ferré, A. Giremus, É. Grivel","doi":"10.5281/ZENODO.44128","DOIUrl":"https://doi.org/10.5281/ZENODO.44128","url":null,"abstract":"In the field of underlay cognitive radio communications, the signal transmitted by the secondary user is disturbed by incoming signals from primary users. Thus, it is necessary to compensate for this secondary-link degradation at the receiver level. In this paper we use Dirichlet process mixtures (DPM) to relax a priori assumptions on the characteristics of the primary user-induced interference. DPM allow us to model the probability density function of the interference. The latter is estimated jointly with the symbols and the channel of the secondary link by using marginalized particle filtering. Our approach makes it possible to improve the symbol error rate compared with an algorithm that simply models the interference as a Gaussian noise.","PeriodicalId":198408,"journal":{"name":"2014 22nd European Signal Processing Conference (EUSIPCO)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127009163","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}
An adaptive waveform selection algorithm for target tracking by multistatic radar/sonar systems in wideband environments is presented to minimize the tracking mean squared error. The proposed selection algorithm is developed based on the minimization of the trace of error covariance matrix for the target state estimates (i.e. the target position and target velocity). This covariance matrix can be computed using the Cramér-Rao lower bounds of the wideband radar/sonar measurements. The performance advantage of the proposed adaptive waveform selection algorithm over the conventional fixed waveforms with minimum and maximum time-bandwidth products is demonstrated by simulation examples using various FM waveform classes.
{"title":"Adaptive waveform selection and target tracking by wideband multistatic radar/sonar systems","authors":"Ngoc Hung Nguyen, K. Doğançay, L. Davis","doi":"10.5281/ZENODO.43859","DOIUrl":"https://doi.org/10.5281/ZENODO.43859","url":null,"abstract":"An adaptive waveform selection algorithm for target tracking by multistatic radar/sonar systems in wideband environments is presented to minimize the tracking mean squared error. The proposed selection algorithm is developed based on the minimization of the trace of error covariance matrix for the target state estimates (i.e. the target position and target velocity). This covariance matrix can be computed using the Cramér-Rao lower bounds of the wideband radar/sonar measurements. The performance advantage of the proposed adaptive waveform selection algorithm over the conventional fixed waveforms with minimum and maximum time-bandwidth products is demonstrated by simulation examples using various FM waveform classes.","PeriodicalId":198408,"journal":{"name":"2014 22nd European Signal Processing Conference (EUSIPCO)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114100736","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}
Stochastic optimization plays an important role in solving many problems encountered in machine learning or adaptive processing. In this context, the second-order statistics of the data are often unknown a priori or their direct computation is too intensive, and they have to be estimated on-line from the related signals. In the context of batch optimization of an objective function being the sum of a data fidelity term and a penalization (e.g. a sparsity promoting function), Majorize-Minimize (MM) subspace methods have recently attracted much interest since they are fast, highly flexible and effective in ensuring convergence. The goal of this paper is to show how these methods can be successfully extended to the case when the cost function is replaced by a sequence of stochastic approximations of it. Simulation results illustrate the good practical performance of the proposed MM Memory Gradient (3MG) algorithm when applied to 2D filter identification.
{"title":"A stochastic 3MG algorithm with application to 2D filter identification","authors":"É. Chouzenoux, J. Pesquet, A. Florescu","doi":"10.5281/ZENODO.44156","DOIUrl":"https://doi.org/10.5281/ZENODO.44156","url":null,"abstract":"Stochastic optimization plays an important role in solving many problems encountered in machine learning or adaptive processing. In this context, the second-order statistics of the data are often unknown a priori or their direct computation is too intensive, and they have to be estimated on-line from the related signals. In the context of batch optimization of an objective function being the sum of a data fidelity term and a penalization (e.g. a sparsity promoting function), Majorize-Minimize (MM) subspace methods have recently attracted much interest since they are fast, highly flexible and effective in ensuring convergence. The goal of this paper is to show how these methods can be successfully extended to the case when the cost function is replaced by a sequence of stochastic approximations of it. Simulation results illustrate the good practical performance of the proposed MM Memory Gradient (3MG) algorithm when applied to 2D filter identification.","PeriodicalId":198408,"journal":{"name":"2014 22nd European Signal Processing Conference (EUSIPCO)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121752326","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}
Assuming a non-stationary Weibull background with no prior knowledge about the presence or not of a clutter edge, we propose and analyze the censoring and detection performances of the automatic censoring Weber-Haykin constant false censoring and alarm rates (ACWH-CFCAR) detector in homogeneous clutter and in the presence of a clutter edge within the reference window. The cfcarness property is assured by use of the Weber-Haykin (WH) adaptive thresholding which bypasses the estimation of the distribution parameters. The censoring algorithm starts up by considering the two most left ranked cells and proceeds forward. The selected homogeneous set is used to estimate the unknown background level. Extensive Monte Carlo simulations show that the performances of the proposed detector are similar to those exhibited by the corresponding fixed-point censoring WH-CFAR detector.
{"title":"Automatic WH-based edge detector in Weibull clutter","authors":"Souad Chabbi, T. Laroussi, A. Mezache","doi":"10.5281/ZENODO.43834","DOIUrl":"https://doi.org/10.5281/ZENODO.43834","url":null,"abstract":"Assuming a non-stationary Weibull background with no prior knowledge about the presence or not of a clutter edge, we propose and analyze the censoring and detection performances of the automatic censoring Weber-Haykin constant false censoring and alarm rates (ACWH-CFCAR) detector in homogeneous clutter and in the presence of a clutter edge within the reference window. The cfcarness property is assured by use of the Weber-Haykin (WH) adaptive thresholding which bypasses the estimation of the distribution parameters. The censoring algorithm starts up by considering the two most left ranked cells and proceeds forward. The selected homogeneous set is used to estimate the unknown background level. Extensive Monte Carlo simulations show that the performances of the proposed detector are similar to those exhibited by the corresponding fixed-point censoring WH-CFAR detector.","PeriodicalId":198408,"journal":{"name":"2014 22nd European Signal Processing Conference (EUSIPCO)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126617602","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}
Compact Descriptors for Visual Search (CDVS) is MPEG proposed standard that will enable efficient and interoperable design of visual search applications using local descriptors. Such descriptors are invariant to rotation and scaling, but are not very robust towards viewpoint changes. In this paper, we address this problem and propose a modified version of the CDVS pipeline that employs image back-projection to compensate for perspective distortion. The proposed technique is based on the homography derived from the correspondence extracted from pairs of matching keypoints. Extensive results show that it improves the CDVS matching accuracy under viewpoint changes while having low complexity.
{"title":"A homography-based CDVS pipeline for image matchingwith improved resilience to viewpoint changes","authors":"Biao Zhao, E. Magli","doi":"10.5281/ZENODO.44189","DOIUrl":"https://doi.org/10.5281/ZENODO.44189","url":null,"abstract":"Compact Descriptors for Visual Search (CDVS) is MPEG proposed standard that will enable efficient and interoperable design of visual search applications using local descriptors. Such descriptors are invariant to rotation and scaling, but are not very robust towards viewpoint changes. In this paper, we address this problem and propose a modified version of the CDVS pipeline that employs image back-projection to compensate for perspective distortion. The proposed technique is based on the homography derived from the correspondence extracted from pairs of matching keypoints. Extensive results show that it improves the CDVS matching accuracy under viewpoint changes while having low complexity.","PeriodicalId":198408,"journal":{"name":"2014 22nd European Signal Processing Conference (EUSIPCO)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123022221","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：