D. Ayllón, R. Gil-Pita, M. Utrilla-Manso, M. Rosa-Zurera
A computationally-efficient single-channel speech enhancement algorithm to improve intelligibility in monaural hearing aids is presented in this paper. The algorithm combines a novel set of features with a simple supervised machine learning technique to estimate the frequency-domain Wiener filter for noise reduction, using extremely low computational resources. Results show a noticeable intelligibility improvement in terms of PESQ score and SNRESI, even for low input SNR, using only a 7% of the computational resources available in a state-of-the-art commercial hearing aid. The performance of the algorithm is comparable to the performance of current algorithms that use more computationally complex features and learning schemas.
{"title":"A computationally-efficient single-channel speech enhancement algorithm for monaural hearing aids","authors":"D. Ayllón, R. Gil-Pita, M. Utrilla-Manso, M. Rosa-Zurera","doi":"10.5281/ZENODO.43843","DOIUrl":"https://doi.org/10.5281/ZENODO.43843","url":null,"abstract":"A computationally-efficient single-channel speech enhancement algorithm to improve intelligibility in monaural hearing aids is presented in this paper. The algorithm combines a novel set of features with a simple supervised machine learning technique to estimate the frequency-domain Wiener filter for noise reduction, using extremely low computational resources. Results show a noticeable intelligibility improvement in terms of PESQ score and SNRESI, even for low input SNR, using only a 7% of the computational resources available in a state-of-the-art commercial hearing aid. The performance of the algorithm is comparable to the performance of current algorithms that use more computationally complex features and learning schemas.","PeriodicalId":198408,"journal":{"name":"2014 22nd European Signal Processing Conference (EUSIPCO)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134215751","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 study proposes a new approach for quantifying complexity of physiological signals characterized by a spectral distribution in modes. Our approach is inspired by wavelet entropy but based on a modal representation: Synchrosqueezing transform. It is calculated for each time sample within the cone of influence of the decomposition. This index is first validated and discussed on simulated multicomponent signals. Finally, it is applied to assess postural control and ability at using all the sensory resources available. Results show significant differences in our index following an induced change in sensory conditions whereas a conventional approach fails. This index may constitute a promising tool for detection of postural troubles.
{"title":"A new approach to wavelet entropy: Application to postural signals","authors":"C. Franco, P. Gumery, A. Fleury, N. Vuillerme","doi":"10.5281/ZENODO.43981","DOIUrl":"https://doi.org/10.5281/ZENODO.43981","url":null,"abstract":"This study proposes a new approach for quantifying complexity of physiological signals characterized by a spectral distribution in modes. Our approach is inspired by wavelet entropy but based on a modal representation: Synchrosqueezing transform. It is calculated for each time sample within the cone of influence of the decomposition. This index is first validated and discussed on simulated multicomponent signals. Finally, it is applied to assess postural control and ability at using all the sensory resources available. Results show significant differences in our index following an induced change in sensory conditions whereas a conventional approach fails. This index may constitute a promising tool for detection of postural troubles.","PeriodicalId":198408,"journal":{"name":"2014 22nd European Signal Processing Conference (EUSIPCO)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121310014","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}
Semidefinite relaxation (SDR) is a powerful approach to solve nonconvex optimization problems involving rank condition. However its performance becomes unacceptable for certain cases. In this paper, a nonconvex equivalent formulation without the rank condition is presented for the broadcast beamforming problem. This new formulation is exploited to obtain an alternating optimization method which is shown to converge to the local optimum rank one solution. Proposed method opens up new possibilities in different applications. Simulations show that the new method is very effective and can attain global optimum especially when the number of users is low.
{"title":"Alternating maximization algorithm for the broadcast beamforming","authors":"Ozlem Tugfe Demir, T. E. Tuncer","doi":"10.5281/ZENODO.43909","DOIUrl":"https://doi.org/10.5281/ZENODO.43909","url":null,"abstract":"Semidefinite relaxation (SDR) is a powerful approach to solve nonconvex optimization problems involving rank condition. However its performance becomes unacceptable for certain cases. In this paper, a nonconvex equivalent formulation without the rank condition is presented for the broadcast beamforming problem. This new formulation is exploited to obtain an alternating optimization method which is shown to converge to the local optimum rank one solution. Proposed method opens up new possibilities in different applications. Simulations show that the new method is very effective and can attain global optimum especially when the number of users is low.","PeriodicalId":198408,"journal":{"name":"2014 22nd European Signal Processing Conference (EUSIPCO)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125231315","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}
Rafael Rodríguez-Sánchez, Francisco D. Igual, José Luis Martínez, R. Mayo, E. S. Quintana‐Ortí
In this paper we evaluate four mainstream video encoders: H.264/MPEG-4 Advanced Video Coding, Google's VP8, High Efficiency Video Coding, and Google's VP9, studying conventional figures-of-merit such as performance in terms of encoded frames per second, and encoding efficiency in both PSNR and bit-rate of the encoded video sequences. Additionally, two platforms equipped with a large number of cores, representative of current multicore architectures for high-end servers, and equipped with a wattmeter allow us to assess the quality of these video encoders in terms of parallel scalability and energy consumption, which is well-founded given the significant levels of thread concurrency and the impact of the power wall in todays' multicore processors.
{"title":"Parallel performance and energy efficiency of modern video encoders on multithreaded architectures","authors":"Rafael Rodríguez-Sánchez, Francisco D. Igual, José Luis Martínez, R. Mayo, E. S. Quintana‐Ortí","doi":"10.5281/ZENODO.43805","DOIUrl":"https://doi.org/10.5281/ZENODO.43805","url":null,"abstract":"In this paper we evaluate four mainstream video encoders: H.264/MPEG-4 Advanced Video Coding, Google's VP8, High Efficiency Video Coding, and Google's VP9, studying conventional figures-of-merit such as performance in terms of encoded frames per second, and encoding efficiency in both PSNR and bit-rate of the encoded video sequences. Additionally, two platforms equipped with a large number of cores, representative of current multicore architectures for high-end servers, and equipped with a wattmeter allow us to assess the quality of these video encoders in terms of parallel scalability and energy consumption, which is well-founded given the significant levels of thread concurrency and the impact of the power wall in todays' multicore processors.","PeriodicalId":198408,"journal":{"name":"2014 22nd European Signal Processing Conference (EUSIPCO)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126419956","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}
Edmond Nurellari, D. McLernon, M. Ghogho, S. Aldalahmeh
We consider the decentralized detection of an unknown deterministic signal in a spatially uncorrelated distributed wireless sensor network. N samples from the signal of interest are gathered by each of the M spatially distributed sensors, and the energy is estimated by each sensor. The sensors send their quantized information over orthogonal channels to the fusion center (FC) which linearly combines them and makes a final decision. We show how by maximizing the modified deflection coefficient we can calculate the optimal transmit power allocation for each sensor and the optimal number of quantization bits to match the channel capacity.
{"title":"Optimal quantization and power allocation for energy-based distributed sensor detection","authors":"Edmond Nurellari, D. McLernon, M. Ghogho, S. Aldalahmeh","doi":"10.5281/ZENODO.43947","DOIUrl":"https://doi.org/10.5281/ZENODO.43947","url":null,"abstract":"We consider the decentralized detection of an unknown deterministic signal in a spatially uncorrelated distributed wireless sensor network. N samples from the signal of interest are gathered by each of the M spatially distributed sensors, and the energy is estimated by each sensor. The sensors send their quantized information over orthogonal channels to the fusion center (FC) which linearly combines them and makes a final decision. We show how by maximizing the modified deflection coefficient we can calculate the optimal transmit power allocation for each sensor and the optimal number of quantization bits to match the channel capacity.","PeriodicalId":198408,"journal":{"name":"2014 22nd European Signal Processing Conference (EUSIPCO)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114870494","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}
G. Papageorgiou, P. Bouboulis, S. Theodoridis, K. Themelis
In this paper, the task of robust estimation in the presence of outliers is presented. Outliers are explicitly modeled by employing sparsity arguments. A novel efficient algorithm, based on the greedy Orthogonal Matching Pursuit (OMP) scheme, is derived. Theoretical results concerning the recovery of the solution as well as simulation experiments, which verify the comparative advantages of the new technique, are discussed.
{"title":"Robust linear regression analysis - The greedy way","authors":"G. Papageorgiou, P. Bouboulis, S. Theodoridis, K. Themelis","doi":"10.5281/ZENODO.44146","DOIUrl":"https://doi.org/10.5281/ZENODO.44146","url":null,"abstract":"In this paper, the task of robust estimation in the presence of outliers is presented. Outliers are explicitly modeled by employing sparsity arguments. A novel efficient algorithm, based on the greedy Orthogonal Matching Pursuit (OMP) scheme, is derived. Theoretical results concerning the recovery of the solution as well as simulation experiments, which verify the comparative advantages of the new technique, are discussed.","PeriodicalId":198408,"journal":{"name":"2014 22nd European Signal Processing Conference (EUSIPCO)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114457553","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 presence of significant levels of signal variability in face-portrait type of images, due to differences in illumination, pose and expression, is generally been accepted as having an adverse effect on the overall performance of i) face modeling and synthesis (FM/S) and also on ii) face recognition (FR) systems. Furthermore, the dependency on such input data variability and thus the sensitivity, with respect to face synthesis performance, of Active Appearance Modeling (AAM), is also well understood. As a result, the Multi-Model Active Appearance Model (MM-AAM) technique [1] has been developed and shown to possess a superior face synthesis performance than AAM. This paper considers the applicability in FR applications of both AAM and MM-AAM face modeling and synthesis approaches. Thus, a MM-AAM methodology has been devised that is tailored to operate successfully within the context of face recognition. Experimental results show FR-MM-AAM to be significantly superior to conventional FR-AAM.
{"title":"On the application of AAM-based systems in face recognition","authors":"M. A. Khan, C. Xydeas, Hassan Ahmed","doi":"10.5281/ZENODO.44192","DOIUrl":"https://doi.org/10.5281/ZENODO.44192","url":null,"abstract":"The presence of significant levels of signal variability in face-portrait type of images, due to differences in illumination, pose and expression, is generally been accepted as having an adverse effect on the overall performance of i) face modeling and synthesis (FM/S) and also on ii) face recognition (FR) systems. Furthermore, the dependency on such input data variability and thus the sensitivity, with respect to face synthesis performance, of Active Appearance Modeling (AAM), is also well understood. As a result, the Multi-Model Active Appearance Model (MM-AAM) technique [1] has been developed and shown to possess a superior face synthesis performance than AAM. This paper considers the applicability in FR applications of both AAM and MM-AAM face modeling and synthesis approaches. Thus, a MM-AAM methodology has been devised that is tailored to operate successfully within the context of face recognition. Experimental results show FR-MM-AAM to be significantly superior to conventional FR-AAM.","PeriodicalId":198408,"journal":{"name":"2014 22nd European Signal Processing Conference (EUSIPCO)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122147353","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 compelling method to calibrate the positions of microphones in an array is with sources at unknown locations. Remarkably, it is possible to reconstruct the locations of both the sources and the receivers, if their number is larger than some prescribed minimum [1, 2]. Existing methods, based on times of arrival or time differences of arrival, only exploit the direct paths between the sources and the receivers. In this proof-of-concept paper, we observe that by placing the whole setup inside a room, we can reduce the number of sources required for calibration. Moreover, our technique allows us to compute the absolute position of the microphone array in the room, as opposed to knowing it up to a rigid transformation or reflection. The key observation is that echoes correspond to virtual sources that we get “for free”. This enables endeavors such as calibrating the array using only a single source.
{"title":"How to localize ten microphones in one finger snap","authors":"Ivan Dokmanić, L. Daudet, M. Vetterli","doi":"10.5281/ZENODO.44162","DOIUrl":"https://doi.org/10.5281/ZENODO.44162","url":null,"abstract":"A compelling method to calibrate the positions of microphones in an array is with sources at unknown locations. Remarkably, it is possible to reconstruct the locations of both the sources and the receivers, if their number is larger than some prescribed minimum [1, 2]. Existing methods, based on times of arrival or time differences of arrival, only exploit the direct paths between the sources and the receivers. In this proof-of-concept paper, we observe that by placing the whole setup inside a room, we can reduce the number of sources required for calibration. Moreover, our technique allows us to compute the absolute position of the microphone array in the room, as opposed to knowing it up to a rigid transformation or reflection. The key observation is that echoes correspond to virtual sources that we get “for free”. This enables endeavors such as calibrating the array using only a single source.","PeriodicalId":198408,"journal":{"name":"2014 22nd European Signal Processing Conference (EUSIPCO)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132317958","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}
Existing approaches to Compressive Sensing (CS) of sparse spectrum has thus far assumed models contaminated with noise (either bounded noise or Gaussian with known power). In practical Cognitive Radio (CR) networks, primary users must be detected even in the presence of low-regulated transmissions from unlicensed systems, which cannot be taken into account in the CS model because of their non-regulated nature. In [1], the authors proposed an overcomplete dictionary that contains tuned spectral shapes of the primary user to sparsely represent the primary users' spectral support, thus allowing all frequency location hypothesis to be jointly evaluated in a global unified optimization framework. Extraction of the primary user frequency locations is then performed based on sparse signal recovery algorithms. Here, we compare different sparse reconstruction strategies and we show through simulation results the link between the interference rejection capabilities and the positive semidefinite character of the residual autocorrelation matrix.
{"title":"Compressed spectrum sensing in the presence of interference: Comparison of sparse recovery strategies","authors":"E. Lagunas, M. Nájar","doi":"10.5281/ZENODO.43898","DOIUrl":"https://doi.org/10.5281/ZENODO.43898","url":null,"abstract":"Existing approaches to Compressive Sensing (CS) of sparse spectrum has thus far assumed models contaminated with noise (either bounded noise or Gaussian with known power). In practical Cognitive Radio (CR) networks, primary users must be detected even in the presence of low-regulated transmissions from unlicensed systems, which cannot be taken into account in the CS model because of their non-regulated nature. In [1], the authors proposed an overcomplete dictionary that contains tuned spectral shapes of the primary user to sparsely represent the primary users' spectral support, thus allowing all frequency location hypothesis to be jointly evaluated in a global unified optimization framework. Extraction of the primary user frequency locations is then performed based on sparse signal recovery algorithms. Here, we compare different sparse reconstruction strategies and we show through simulation results the link between the interference rejection capabilities and the positive semidefinite character of the residual autocorrelation matrix.","PeriodicalId":198408,"journal":{"name":"2014 22nd European Signal Processing Conference (EUSIPCO)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130331548","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 use a stochastic diffusion equation for the reconstruction of binary tomography cross-sections obtained from a small number of projections. The aim of this new method is to escape from local minima by changing the shape of the boundaries of the image. First, an initial binary image is reconstructed with a deterministic Total Variation regularization method, and then this binary reconstructed image is refined by a stochastic partial differential equation with singular diffusivity and a gradient dependent noise. This method is tested on a 256 × 256 experimental micro-CT trabecular bone image with different additive Gaussian noises. The reconstruction images are clearly improved.
{"title":"Bone microstructure reconstructions from few projections with stochastic nonlinear diffusion","authors":"L. Wang, B. Sixou, F. Peyrin","doi":"10.5281/ZENODO.44155","DOIUrl":"https://doi.org/10.5281/ZENODO.44155","url":null,"abstract":"In this work, we use a stochastic diffusion equation for the reconstruction of binary tomography cross-sections obtained from a small number of projections. The aim of this new method is to escape from local minima by changing the shape of the boundaries of the image. First, an initial binary image is reconstructed with a deterministic Total Variation regularization method, and then this binary reconstructed image is refined by a stochastic partial differential equation with singular diffusivity and a gradient dependent noise. This method is tested on a 256 × 256 experimental micro-CT trabecular bone image with different additive Gaussian noises. The reconstruction images are clearly improved.","PeriodicalId":198408,"journal":{"name":"2014 22nd European Signal Processing Conference (EUSIPCO)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114090573","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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