Alina Santillán-Guzmán, M. Fischer, U. Heute, G. Schmidt
Electroencephalography (EEG) recordings are used for brain research. However, in most cases, the recordings not only contain brain waves, but also artifacts of physiological or technical origins. A recent approach used for signal enhancement is Empirical Mode Decomposition (EMD), an adaptive data-driven technique which decomposes non-stationary data into so-called Intrinsic Mode Functions (IMFs). Once the IMFs are obtained, they can be used for denoising and detrending purposes. This paper presents a real-time implementation of an EMD-based signal enhancement scheme. The proposed implementation is used for removing noise, for suppressing muscle artifacts, and for detrending EEG signals in an automatic manner and in real-time. The proposed algorithm is demonstrated by application to a simulated and a real EEG data set from an epilepsy patient. Moreover, by visual inspection and in a quantitative manner, it is shown that after the EMD in real-time, the EEG signals are enhanced.
{"title":"Real-time Empirical Mode Decomposition for EEG signal enhancement","authors":"Alina Santillán-Guzmán, M. Fischer, U. Heute, G. Schmidt","doi":"10.5281/ZENODO.43399","DOIUrl":"https://doi.org/10.5281/ZENODO.43399","url":null,"abstract":"Electroencephalography (EEG) recordings are used for brain research. However, in most cases, the recordings not only contain brain waves, but also artifacts of physiological or technical origins. A recent approach used for signal enhancement is Empirical Mode Decomposition (EMD), an adaptive data-driven technique which decomposes non-stationary data into so-called Intrinsic Mode Functions (IMFs). Once the IMFs are obtained, they can be used for denoising and detrending purposes. This paper presents a real-time implementation of an EMD-based signal enhancement scheme. The proposed implementation is used for removing noise, for suppressing muscle artifacts, and for detrending EEG signals in an automatic manner and in real-time. The proposed algorithm is demonstrated by application to a simulated and a real EEG data set from an epilepsy patient. Moreover, by visual inspection and in a quantitative manner, it is shown that after the EMD in real-time, the EEG signals are enhanced.","PeriodicalId":400766,"journal":{"name":"21st European Signal Processing Conference (EUSIPCO 2013)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129390619","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}
O. Cherrak, H. Ghennioui, El Hossein Abarkan, N. Thirion-Moreau
This communication addresses the problem of the Non-Unitary Joint Block Diagonalization (NU - JBD) of a given set of complexmatrices. This problemoccurs in various fields of applications, among which is the blind separation of convolutive mixtures of sources. We present a new method for the NU - JBD based on the Levenberg-Marquardt algorithm (LMA). Our algorithm uses a numerical diagram of optimization which requires the calculation of the complex Hessian matrices. The main advantages of the proposed method stem from the LMA properties: it is powerful, stable and more robust. Computer simulations are provided in order to illustrate the good behavior of the proposed method in different contexts. Two cases are studied: in the first scenario, a set of exactly block-diagonal matrices are considered, then these matrices are progressively perturbed by an additive gaussian noise. Finally, this new NU - JBD algorithm is compared to others put forward in the literature: one based on an optimal step-size relative gradient-descent algorithm [1] and one based on a nonlinear conjugate gradient algorithm [2]. This comparison emphasizes the good behavior of the proposed method.
{"title":"Non-Unitary Joint Block Diagonalization of matrices using a Levenberg-Marquardt algorithm","authors":"O. Cherrak, H. Ghennioui, El Hossein Abarkan, N. Thirion-Moreau","doi":"10.5281/ZENODO.43369","DOIUrl":"https://doi.org/10.5281/ZENODO.43369","url":null,"abstract":"This communication addresses the problem of the Non-Unitary Joint Block Diagonalization (NU - JBD) of a given set of complexmatrices. This problemoccurs in various fields of applications, among which is the blind separation of convolutive mixtures of sources. We present a new method for the NU - JBD based on the Levenberg-Marquardt algorithm (LMA). Our algorithm uses a numerical diagram of optimization which requires the calculation of the complex Hessian matrices. The main advantages of the proposed method stem from the LMA properties: it is powerful, stable and more robust. Computer simulations are provided in order to illustrate the good behavior of the proposed method in different contexts. Two cases are studied: in the first scenario, a set of exactly block-diagonal matrices are considered, then these matrices are progressively perturbed by an additive gaussian noise. Finally, this new NU - JBD algorithm is compared to others put forward in the literature: one based on an optimal step-size relative gradient-descent algorithm [1] and one based on a nonlinear conjugate gradient algorithm [2]. This comparison emphasizes the good behavior of the proposed method.","PeriodicalId":400766,"journal":{"name":"21st European Signal Processing Conference (EUSIPCO 2013)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132432408","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}
Many communication systems based on the synchronism of chaotic systems have been proposed as an alternative spread spectrum modulation that improves the level of privacy in data transmission. However, due to the lack of robustness of chaos synchronization, even minor channel imperfections are enough to hinder communication. In this paper, we propose an adaptive equalization scheme to recover a binary sequence modulated by a chaotic signal, which in turn is generated by Ikeda maps. The proposed scheme employs the normalized least-mean-squares (NLMS) algorithm with a modification to enable chaotic synchronization even when the communication channel is not ideal. Simulation results show that the modified NLMS can successfully equalize the channel in different scenarios.
{"title":"Channel equalization for synchronization of Ikeda maps","authors":"Renato Candido, M. Eisencraft, Magno T. M. Silva","doi":"10.5281/ZENODO.43581","DOIUrl":"https://doi.org/10.5281/ZENODO.43581","url":null,"abstract":"Many communication systems based on the synchronism of chaotic systems have been proposed as an alternative spread spectrum modulation that improves the level of privacy in data transmission. However, due to the lack of robustness of chaos synchronization, even minor channel imperfections are enough to hinder communication. In this paper, we propose an adaptive equalization scheme to recover a binary sequence modulated by a chaotic signal, which in turn is generated by Ikeda maps. The proposed scheme employs the normalized least-mean-squares (NLMS) algorithm with a modification to enable chaotic synchronization even when the communication channel is not ideal. Simulation results show that the modified NLMS can successfully equalize the channel in different scenarios.","PeriodicalId":400766,"journal":{"name":"21st European Signal Processing Conference (EUSIPCO 2013)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130095615","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}
H. Dahrouj, Wei Yu, Taiwen Tang, J. Chow, Radu Selea
Coordinated resource allocation is a topic of significant interest for emerging wireless networks. This paper proposes and examines the benefits of coordinated scheduling in soft frequency reuse (SFR) based systems. Consider the downlink of a 3-sector-per-cell SFR-based wireless backhaul network consisting of N access nodes (ANs), each serving K remote terminals (RTs) multiplexed across the K time/frequency zones, with frequency reuse one between the sectors. Assuming a fixed transmit power, the paper considers the resource allocation problem of optimally scheduling each of the NK RTs to one of the NK power-zones, on a one-to-one basis, and in a coordinated manner, as opposed to conventional systems which schedule the RTs one at a time in an uncoordinated way. The paper solves the problem using the auction method, which offers a close-to-global-optimal solution. The paper further proposes heuristic methods with lower computational complexity. Simulation results show that coordinated scheduling offers significant performance improvement as compared to non-coordinated systems.
{"title":"Coordinated scheduling for wireless backhaul networks with soft frequency reuse","authors":"H. Dahrouj, Wei Yu, Taiwen Tang, J. Chow, Radu Selea","doi":"10.5281/ZENODO.43543","DOIUrl":"https://doi.org/10.5281/ZENODO.43543","url":null,"abstract":"Coordinated resource allocation is a topic of significant interest for emerging wireless networks. This paper proposes and examines the benefits of coordinated scheduling in soft frequency reuse (SFR) based systems. Consider the downlink of a 3-sector-per-cell SFR-based wireless backhaul network consisting of N access nodes (ANs), each serving K remote terminals (RTs) multiplexed across the K time/frequency zones, with frequency reuse one between the sectors. Assuming a fixed transmit power, the paper considers the resource allocation problem of optimally scheduling each of the NK RTs to one of the NK power-zones, on a one-to-one basis, and in a coordinated manner, as opposed to conventional systems which schedule the RTs one at a time in an uncoordinated way. The paper solves the problem using the auction method, which offers a close-to-global-optimal solution. The paper further proposes heuristic methods with lower computational complexity. Simulation results show that coordinated scheduling offers significant performance improvement as compared to non-coordinated systems.","PeriodicalId":400766,"journal":{"name":"21st European Signal Processing Conference (EUSIPCO 2013)","volume":"457 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123204161","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}
A. Tamim, K. Minaoui, K. Daoudi, Hussein M. Yahia, A. Atillah, M. F. Smiej, D. Aboutajdine
In this work, we aim to develop a simple and fast algorithm using conventional methods in images segmentation for the automatic detection and extraction of upwelling areas, in the coastal region of Morocco, from the sea surface temperature (SST) satellite images. Our approach is based on the evaluation and comparison between two unsupervised classification methods, Otsu and Fuzzy C-means, and explores the applicability of these methods to our classification problem. The latter consists in coarse detection of the main thermal front that separates coastal cold upwelling waters from the remaining ocean waters. The algorithm has been applied and validated by an oceanographer over a database of 66 SST images corresponding to southern Moroccan coastal upwelling of the years 2004, 2005, 2007 and 2009. The results indicate that the proposed algorithm revealed is promising and reliable on different upwelling scenarios and for a wide variety of oceanographic conditions.
{"title":"A simple and efficient approach for coarse segmentation of Moroccan coastal upwelling","authors":"A. Tamim, K. Minaoui, K. Daoudi, Hussein M. Yahia, A. Atillah, M. F. Smiej, D. Aboutajdine","doi":"10.5281/ZENODO.43637","DOIUrl":"https://doi.org/10.5281/ZENODO.43637","url":null,"abstract":"In this work, we aim to develop a simple and fast algorithm using conventional methods in images segmentation for the automatic detection and extraction of upwelling areas, in the coastal region of Morocco, from the sea surface temperature (SST) satellite images. Our approach is based on the evaluation and comparison between two unsupervised classification methods, Otsu and Fuzzy C-means, and explores the applicability of these methods to our classification problem. The latter consists in coarse detection of the main thermal front that separates coastal cold upwelling waters from the remaining ocean waters. The algorithm has been applied and validated by an oceanographer over a database of 66 SST images corresponding to southern Moroccan coastal upwelling of the years 2004, 2005, 2007 and 2009. The results indicate that the proposed algorithm revealed is promising and reliable on different upwelling scenarios and for a wide variety of oceanographic conditions.","PeriodicalId":400766,"journal":{"name":"21st European Signal Processing Conference (EUSIPCO 2013)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121750074","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 work presents an exact tracking analysis of the Normalized Least Mean Square (NLMS) algorithm for circular complex correlated Gaussian inputs. Unlike the existing works, the analysis presented neither uses separation principle nor small step-size assumption. The approach is based on the derivation of a closed form expression for the cumulative distribution function (CDF) of random variables of the form (∥u∥D12)(∥u∥D22)-1 where u is a white Gaussian vector and D1 and D2 are diagonal matrices and using that to derive the first and second moments of such variables. These moments are then used to evaluate the tracking behavior of the NLMS algorithm in closed form. Thus, both the steady-state mean-square-error (MSE) and mean-square-deviation (MSD )tracking behaviors of the NLMS algorithm are evaluated. The analysis is also used to derive the optimum step-size that minimizes the excess MSE (EMSE). Simulations presented for the steady-state tracking behavior support the theoretical findings for a wide range of step-size and input correlation.
{"title":"Exact tracking analysis of the NLMS algorithm for correlated Gaussian inputs","authors":"T. Al-Naffouri, M. Moinuddin","doi":"10.5281/ZENODO.43671","DOIUrl":"https://doi.org/10.5281/ZENODO.43671","url":null,"abstract":"This work presents an exact tracking analysis of the Normalized Least Mean Square (NLMS) algorithm for circular complex correlated Gaussian inputs. Unlike the existing works, the analysis presented neither uses separation principle nor small step-size assumption. The approach is based on the derivation of a closed form expression for the cumulative distribution function (CDF) of random variables of the form (∥u∥D12)(∥u∥D22)-1 where u is a white Gaussian vector and D1 and D2 are diagonal matrices and using that to derive the first and second moments of such variables. These moments are then used to evaluate the tracking behavior of the NLMS algorithm in closed form. Thus, both the steady-state mean-square-error (MSE) and mean-square-deviation (MSD )tracking behaviors of the NLMS algorithm are evaluated. The analysis is also used to derive the optimum step-size that minimizes the excess MSE (EMSE). Simulations presented for the steady-state tracking behavior support the theoretical findings for a wide range of step-size and input correlation.","PeriodicalId":400766,"journal":{"name":"21st European Signal Processing Conference (EUSIPCO 2013)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127531275","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}
Spatial sound acquisition methods typically capture the sound scene with reference to the position of the recording device. Using a recently proposed virtual microphone (VM) technique, the position and characteristics of the recording device (such as the directivity response and orientation) can be modified. This technique relies on synthesizing a VM signal at an arbitrary position, which sounds perceptually similar to the signal that would be recorded with a physical microphone placed at the same location. In this paper, we present a method to generate a VM signal in the presence of noise. Noise reduction is accomplished using a parametric multichannel Wiener filter, where a trade-off parameter is applied in order to achieve a constant residual noise level in the generated VM signal, irrespective of the VM position. The simulated experiments show the applicability of the method for signal extraction in the presence of additive noise.
{"title":"Generating virtual microphone signals in noisy environments","authors":"K. Kowalczyk, A. Craciun, Emanuël Habets","doi":"10.5281/ZENODO.43505","DOIUrl":"https://doi.org/10.5281/ZENODO.43505","url":null,"abstract":"Spatial sound acquisition methods typically capture the sound scene with reference to the position of the recording device. Using a recently proposed virtual microphone (VM) technique, the position and characteristics of the recording device (such as the directivity response and orientation) can be modified. This technique relies on synthesizing a VM signal at an arbitrary position, which sounds perceptually similar to the signal that would be recorded with a physical microphone placed at the same location. In this paper, we present a method to generate a VM signal in the presence of noise. Noise reduction is accomplished using a parametric multichannel Wiener filter, where a trade-off parameter is applied in order to achieve a constant residual noise level in the generated VM signal, irrespective of the VM position. The simulated experiments show the applicability of the method for signal extraction in the presence of additive noise.","PeriodicalId":400766,"journal":{"name":"21st European Signal Processing Conference (EUSIPCO 2013)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126681979","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}
The harmonic model, i.e., a sum of sinusoids having frequencies that are integer multiples of the pitch, has been widely used for modeling of voiced speech. In microphone arrays, the direction-of-arrival (DOA) adds an additional parameter that can help in obtaining a robust procedure for tracking non-stationary speech signals in noisy conditions. In this paper, a joint DOA and pitch estimation (JDPE) method is proposed. The method is based on the minimum variance distortionless response (MVDR) beamformer in the frequency-domain and is much faster than previous joint methods, as it only requires the computation of the optimal filters once per segment. To exploit that both pitch and DOA evolve piece-wise smoothly over time, we also extend a dynamic programming approach to joint smoothing of both parameters. Simulations show the proposed method is much more robust than parallel and cascaded methods combining existing DOA and pitch estimators.
{"title":"Fast joint DOA and pitch estimation using a broadband MVDR beamformer","authors":"Sam Karimian-Azari, J. Jensen, M. G. Christensen","doi":"10.5281/ZENODO.43553","DOIUrl":"https://doi.org/10.5281/ZENODO.43553","url":null,"abstract":"The harmonic model, i.e., a sum of sinusoids having frequencies that are integer multiples of the pitch, has been widely used for modeling of voiced speech. In microphone arrays, the direction-of-arrival (DOA) adds an additional parameter that can help in obtaining a robust procedure for tracking non-stationary speech signals in noisy conditions. In this paper, a joint DOA and pitch estimation (JDPE) method is proposed. The method is based on the minimum variance distortionless response (MVDR) beamformer in the frequency-domain and is much faster than previous joint methods, as it only requires the computation of the optimal filters once per segment. To exploit that both pitch and DOA evolve piece-wise smoothly over time, we also extend a dynamic programming approach to joint smoothing of both parameters. Simulations show the proposed method is much more robust than parallel and cascaded methods combining existing DOA and pitch estimators.","PeriodicalId":400766,"journal":{"name":"21st European Signal Processing Conference (EUSIPCO 2013)","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115003297","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}
The Generalized Complex time distributions have been recently introduced as a way for reducing the auto-terms of any bilinear time-frequency representation that appear when dealing with non-linear time-frequency structures. This concept requires the definition of signal at complex times and this abstract operation is achieved by the analytical continuation principle. In the current version, this principle is efficient only for narrow-band signals, restricting also the application of the complex time distribution to more complicate signals. The purpose of this paper is to propose a method to overcome the limitations of the analytical continuation in the case of signals with a spread time-frequency variation. This method is based on the compression of the signals spectrum to a bandwidth that ensures the efficiency of the analytical continuation technique. Then, the application of generalized complex time distribution will allow an accurate estimation of the instantaneous frequency law. The spectrum expanding will bring this estimation to the correct time-frequency location.
{"title":"Generalized Complex time-distribution using modified analytical continuation","authors":"Cindy Bernard, C. Ioana","doi":"10.5281/ZENODO.43674","DOIUrl":"https://doi.org/10.5281/ZENODO.43674","url":null,"abstract":"The Generalized Complex time distributions have been recently introduced as a way for reducing the auto-terms of any bilinear time-frequency representation that appear when dealing with non-linear time-frequency structures. This concept requires the definition of signal at complex times and this abstract operation is achieved by the analytical continuation principle. In the current version, this principle is efficient only for narrow-band signals, restricting also the application of the complex time distribution to more complicate signals. The purpose of this paper is to propose a method to overcome the limitations of the analytical continuation in the case of signals with a spread time-frequency variation. This method is based on the compression of the signals spectrum to a bandwidth that ensures the efficiency of the analytical continuation technique. Then, the application of generalized complex time distribution will allow an accurate estimation of the instantaneous frequency law. The spectrum expanding will bring this estimation to the correct time-frequency location.","PeriodicalId":400766,"journal":{"name":"21st European Signal Processing Conference (EUSIPCO 2013)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115020259","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}
A time-quefrency dereverberation method for reducing the minimum-phase component (MPC) of the room impulse response (RIR) is presented. This paper shows that the vocaltract and glottal components and the MPC of the RIR can be eliminated from observed signals convolving the unknown RIR with an unknown voiced speech signal. The liftered sequence is applied to direction-of-arrival (DOA) estimator with the multiple signal classification (MUSIC) procedure. Computer simulations demonstrate the superiority of the our cepstral prefiltering approach.
{"title":"A cepstrum prefiltering approach for DOA estimation of speech signal in reverberant environments","authors":"Ryudo Nagase, K. Oishi, T. Furukawa","doi":"10.5281/ZENODO.43435","DOIUrl":"https://doi.org/10.5281/ZENODO.43435","url":null,"abstract":"A time-quefrency dereverberation method for reducing the minimum-phase component (MPC) of the room impulse response (RIR) is presented. This paper shows that the vocaltract and glottal components and the MPC of the RIR can be eliminated from observed signals convolving the unknown RIR with an unknown voiced speech signal. The liftered sequence is applied to direction-of-arrival (DOA) estimator with the multiple signal classification (MUSIC) procedure. Computer simulations demonstrate the superiority of the our cepstral prefiltering approach.","PeriodicalId":400766,"journal":{"name":"21st European Signal Processing Conference (EUSIPCO 2013)","volume":"01 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130162607","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}
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