Results 11 to 20 of about 77,863 (306)
A unified approach to sparse signal processing [PDF]
Eurasip Journal on Advances in Signal Processing, 2012 A unified view of the area of sparse signal processing is presented in tutorial form by bringing together various fields in which the property of sparsity has been successfully exploited. For each of these fields, various algorithms and techniques, which have been developed to leverage sparsity, are described succinctly.
Farokh Marvasti +2 more
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Sparse Signal Processing Concepts for Efficient 5G System Design
IEEE Access, 2015 As it becomes increasingly apparent that 4G will not be able to meet the emerging demands of future mobile communication systems, the question what could make up a 5G system, what are the crucial challenges, and what are the key drivers is part of ...
Gerhard Wunder +3 more
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On Sparse Methods for Array Signal Processing in the Presence of Interference
IEEE Antennas and Wireless Propagation Letters, 2015 We analyze the performance of several algorithms designed to solve the inverse sparse problem when they are applied to array signal processing. Specifically we study the error on the estimation of the complex envelope and the direction of arrival of signals of interest in the presence of interference sources using a uniform linear array. In particular,
Sebastian Pazos +2 more
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IEEE Access, 2018 In the past decade, sparse and low-rank recovery has drawn much attention in many areas such as signal/image processing, statistics, bioinformatics, and machine learning.
Fei Wen +3 more
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Filtered Variation method for denoising and sparse signal processing [PDF]
2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2012 We propose a new framework, called Filtered Variation (FV), for denoising and sparse signal processing applications. These problems are inherently ill-posed. Hence, we provide regularization to overcome this challenge by using discrete time filters that are widely used in signal processing.
Kivanç Köse +2 more
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Sparse representations and sphere decoding for array signal processing
Digital Signal Processing, 2012 Array processing algorithms are used in many applications for source localization and signal waveform estimation. When the number of snapshots is small and/or the signal-to-noise ratio (SNR) is low, it becomes a challenge to discriminate closely-spaced sources.
Tarik Yardibi +3 more
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Method of Range Ambiguity Suppression Combining Sparse Reconstruction and Matched Filter
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022 Synthetic aperture radar (SAR) images are often affected by range ambiguity due to antenna sidelobe characteristics and pulse operating mechanism. The work of range ambiguity suppression focuses on both SAR system design and signal processing. On the one
Meng Qi +4 more
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Frame coherence and sparse signal processing [PDF]
2011 IEEE International Symposium on Information Theory Proceedings, 2011 The sparse signal processing literature often uses random sensing matrices to obtain performance guarantees. Unfortunately, in the real world, sensing matrices do not always come from random processes. It is therefore desirable to evaluate whether an arbitrary matrix, or frame, is suitable for sensing sparse signals.
Dustin G. Mixon +2 more
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A Multi-Source Separation Approach Based on DOA Cue and DNN
Applied Sciences, 2022 Multiple sound source separation in a reverberant environment has become popular in recent years. To improve the quality of the separated signal in a reverberant environment, a separation method based on a DOA cue and a deep neural network (DNN) is ...
Yu Zhang +3 more
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Sparse approximations in signal and image processing [PDF]
Signal Processing, 2006 Guest editorial of the special issue on Sparse Approximations in Signal and Image ...
Rémi Gribonval, Morten Nielsen 0002
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