Spatial Spectrum estimation is a key technique used in a wide variety of problems arising in signal processing and communication, particularly those employing multiple antennas. In many scenarios such as direction finding using antenna arrays, it is crucial to estimate which directions in space contribute to active sources (indicated by a non zero power). It has been recently shown that if the sources from different directions are statistically uncorrelated, it is possible to identify as many as O(M2) active sources using only M physical antennas. A sparse representation for the spatial spectrum was further exploited to reconstruct the spectrum using convex optimization techniques. In this paper, we consider the situation when there is non zero cross correlation between the sources impinging from different directions. We investigate if, fundamentally, it still possible to identify more sources than the number of physical sensors and what role the cross correlation terms play. Recovery guarantees are developed to ensure uniqueness of the sparse representation for spectrum sensing. They are further extended to establish conditions under which a greedy heuristic, namely the Orthogonal Matching Pursuit algorithm will successfully recover the sparse spectrum. It is shown that in both cases, it is possible to recover support of larger size provided the correlation terms are small compared to the power of the impinging signals.
{"title":"Conditions for identifiability in sparse spatial spectrum sensing","authors":"P. Pal, P. Vaidyanathan","doi":"10.5281/ZENODO.43683","DOIUrl":"https://doi.org/10.5281/ZENODO.43683","url":null,"abstract":"Spatial Spectrum estimation is a key technique used in a wide variety of problems arising in signal processing and communication, particularly those employing multiple antennas. In many scenarios such as direction finding using antenna arrays, it is crucial to estimate which directions in space contribute to active sources (indicated by a non zero power). It has been recently shown that if the sources from different directions are statistically uncorrelated, it is possible to identify as many as O(M2) active sources using only M physical antennas. A sparse representation for the spatial spectrum was further exploited to reconstruct the spectrum using convex optimization techniques. In this paper, we consider the situation when there is non zero cross correlation between the sources impinging from different directions. We investigate if, fundamentally, it still possible to identify more sources than the number of physical sensors and what role the cross correlation terms play. Recovery guarantees are developed to ensure uniqueness of the sparse representation for spectrum sensing. They are further extended to establish conditions under which a greedy heuristic, namely the Orthogonal Matching Pursuit algorithm will successfully recover the sparse spectrum. It is shown that in both cases, it is possible to recover support of larger size provided the correlation terms are small compared to the power of the impinging signals.","PeriodicalId":400766,"journal":{"name":"21st European Signal Processing Conference (EUSIPCO 2013)","volume":"43 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":"129086093","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 novel compound Structural Health Monitoring (SHM) method as well as some signal processing and communication challenges for a robust methodology are presented in this paper. The performance of the two-step SHM method is compared to some other established damage detection techniques. The proposed method was found to identify the location of local damage more accurately than the other methods. Significant signal processing and communication aspects still need to be addressed in order to enhance the robustness of the method.
{"title":"Damage assessment of bridges using compound SHM- signal processing and communication challenges","authors":"R. Soman, T. Onoufriou, M. Kyriakides","doi":"10.5281/ZENODO.43611","DOIUrl":"https://doi.org/10.5281/ZENODO.43611","url":null,"abstract":"A novel compound Structural Health Monitoring (SHM) method as well as some signal processing and communication challenges for a robust methodology are presented in this paper. The performance of the two-step SHM method is compared to some other established damage detection techniques. The proposed method was found to identify the location of local damage more accurately than the other methods. Significant signal processing and communication aspects still need to be addressed in order to enhance the robustness of the method.","PeriodicalId":400766,"journal":{"name":"21st European Signal Processing Conference (EUSIPCO 2013)","volume":"67 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":"130812862","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}
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}
The Distributed Video Coding (DVC) paradigm is suitable for devices which have limited encoding capabilities. However, it is characterized by excessive decoding delays which compromise their application for time constrained services. This limitation can be mitigated by adopting parallel DVC architectures. Yet, the traditional Gray-code or binary-code representations have a non-uniform distribution of mismatch across bit-planes, resulting in uneven decoding times which hinder parallel decoding. This work proposes an alternative indexing scheme, where mismatch is distributed more uniformly amongst bit-planes and thus comparable decoding delays are expected, facilitating parallel implementations. This method reduces decoding time by up to 32% compared to architectures using simple parallel techniques, with a slight loss of 0.06dB in RD performance.
{"title":"Improving decoding speed for parallel Distributed Video Coding architectures","authors":"Jeffrey J. Micallef, R. Farrugia, C. J. Debono","doi":"10.5281/ZENODO.43421","DOIUrl":"https://doi.org/10.5281/ZENODO.43421","url":null,"abstract":"The Distributed Video Coding (DVC) paradigm is suitable for devices which have limited encoding capabilities. However, it is characterized by excessive decoding delays which compromise their application for time constrained services. This limitation can be mitigated by adopting parallel DVC architectures. Yet, the traditional Gray-code or binary-code representations have a non-uniform distribution of mismatch across bit-planes, resulting in uneven decoding times which hinder parallel decoding. This work proposes an alternative indexing scheme, where mismatch is distributed more uniformly amongst bit-planes and thus comparable decoding delays are expected, facilitating parallel implementations. This method reduces decoding time by up to 32% compared to architectures using simple parallel techniques, with a slight loss of 0.06dB in RD performance.","PeriodicalId":400766,"journal":{"name":"21st European Signal Processing Conference (EUSIPCO 2013)","volume":"47 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":"127213559","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 unsupervised track classification approach is applied to sonar multistatic multitarget tracking. Appropriate discriminative and aggregative features are derived from beamformed and normalized matched-filtered data as recorded from a linear array towed behind an AUV. A clustering algorithm based on Hierarchical Dirichlet Processes is proposed for unsupervised classification of tracks. Overall improvement of target tracking is demonstrated via the Optimal Subpattern Assignment metric.
{"title":"Unsupervised track classification based on Hierarchical Dirichlet Processes","authors":"J. Sildam, P. Braca, K. LePage, P. Willett","doi":"10.5281/ZENODO.43744","DOIUrl":"https://doi.org/10.5281/ZENODO.43744","url":null,"abstract":"An unsupervised track classification approach is applied to sonar multistatic multitarget tracking. Appropriate discriminative and aggregative features are derived from beamformed and normalized matched-filtered data as recorded from a linear array towed behind an AUV. A clustering algorithm based on Hierarchical Dirichlet Processes is proposed for unsupervised classification of tracks. Overall improvement of target tracking is demonstrated via the Optimal Subpattern Assignment metric.","PeriodicalId":400766,"journal":{"name":"21st European Signal Processing Conference (EUSIPCO 2013)","volume":"13 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":"125601308","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}
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}
This paper develops a linear predictor for application to wind speed and direction forecasting in time and across different sites. The wind speed and direction are modelled via the magnitude and phase of a complex-valued time-series. A multichannel adaptive filter is set to predict this signal, based on its past values and the spatio-temporal correlation between wind signals measured at numerous geographical locations. The time-varying nature of the underlying system and the annual cycle of seasons motivates the development of a cyclostationary Wiener filter, which is tested on hourly mean wind speed and direction data from 13 weather stations across the UK, and shown to provide an improvement over both stationary Wiener filtering and a recent auto-regressive approach.
{"title":"A cyclo-stationary complex multichannelwiener filter for the prediction of wind speed and direction","authors":"J. Dowell, Stepha Weiss, D. Hill, D. Infield","doi":"10.5281/ZENODO.43678","DOIUrl":"https://doi.org/10.5281/ZENODO.43678","url":null,"abstract":"This paper develops a linear predictor for application to wind speed and direction forecasting in time and across different sites. The wind speed and direction are modelled via the magnitude and phase of a complex-valued time-series. A multichannel adaptive filter is set to predict this signal, based on its past values and the spatio-temporal correlation between wind signals measured at numerous geographical locations. The time-varying nature of the underlying system and the annual cycle of seasons motivates the development of a cyclostationary Wiener filter, which is tested on hourly mean wind speed and direction data from 13 weather stations across the UK, and shown to provide an improvement over both stationary Wiener filtering and a recent auto-regressive approach.","PeriodicalId":400766,"journal":{"name":"21st European Signal Processing Conference (EUSIPCO 2013)","volume":"49 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":"117274310","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}
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}
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