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Optimized signal expansions for sparse representation
IEEE Transactions on Signal Processing, 2001Traditional signal decompositions such as transforms, filterbanks, and wavelets generate signal expansions using the analysis-synthesis setting: the expansion coefficients are found by taking the inner product of the signal with the corresponding analysis vector.
Sven Ole Aase +3 more
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Design of signal expansions for sparse representation
2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100), 2002Traditional signal decompositions generate signal expansions using the analysis-synthesis setting: the expansion coefficients are found by taking the inner product of the signal with the corresponding analysis vector. In this paper we try to free ourselves from the analysis-synthesis paradigm by concentrating on the synthesis or reconstruction part of ...
Sven Ole Aase +3 more
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Homotopy continuation for sparse signal representation
Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005., 2006We explore the application of a homotopy continuation-based method for sparse signal representation in overcomplete dictionaries. Our problem setup is based on the basis pursuit framework, which involves a convex optimization problem consisting of terms enforcing data fidelity and sparsity, balanced by a regularization parameter.
Dmitry M. Malioutov +2 more
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Quantitative Optoacoustic Signal Extraction Using Sparse Signal Representation
IEEE Transactions on Medical Imaging, 2009We report on a new quantification methodology of optoacoustic tomographic reconstructions under heterogeneous illumination conditions representative of realistic whole-body imaging scenarios. Our method relies on the differences in the spatial characteristics of the absorption coefficient and the optical energy density within the medium.
Amir Rosenthal +2 more
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Sparse signal representation for MIMO radar imaging
2008 42nd Asilomar Conference on Signals, Systems and Computers, 2008MIMO radar can achieve superior performance over the conventional phased-array radar through waveform diversity. Considerations in transmit waveform and receive filter design are central to attaining improved performance through a MIMO system. Moreover, adaptive array techniques are needed to improve accuracy, resolution and to further provide ...
William Roberts +4 more
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Comparison of Methods for Sparse Representation of Music Signals
Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005., 2006Within the last few decades, several new signal processing tools have appeared. These have mainly been compared using constructed signals, signals designed to show the advantage of a new method over already existing methods. We evaluate the following methods on "real" signals: basis pursuit; minimum fuel neural networks; matching pursuit; best ...
Line Ørtoft Endelt +1 more
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Sparse Adaptive Representations for Musical Signals
2007Musical signals are, strictly speaking, acoustic signals where some aesthetically relevant information is conveyed through propagating pressure waves. Although the human auditory system exhibits a remarkable ability to interpret and understand these sound waves, these types of signals cannot be processed as such by computers.
Daudet, Laurent, Torrésani, Bruno
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The farey-dictionary for sparse representation of periodic signals
2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2014A finite duration sequence exhibiting periodicities does not in general admit a sparse representation in terms of the DFT basis unless the period is a divisor of the duration. This paper develops a dictionary called the Farey dictionary for the efficient representation of such sequences.
Vaidyanathan, P. P., Pal, Piya
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Sparse Representation of GPR Traces With Application to Signal Classification
IEEE Transactions on Geoscience and Remote Sensing, 2013 Sparse representation (SR) models a signal with a small number of elementary waves using an overcomplete dictionary. It has been employed for a wide range of signal and image processing applications, including denoising, deblurring, and compression.
Wenbin Shao +2 more
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Auditory-inspired sparse representation of audio signals
Speech Communication, 2011This article deals with the generation of auditory-inspired spectro-temporal features aimed at audio coding. To do so, we first generate sparse audio representations we call spikegrams, using projections on gammatone/gammachirp kernels that generate neural spikes.
Ramin Pichevar +3 more
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