Atomic Decomposition by Basis Pursuit
SIAM Journal on Scientific Computing
Coding time-varying signals using sparse, shift-invariant representations
Proceedings of the 1998 conference on Advances in neural information processing systems II
Probabilistic matching pursuit with Gabor dictionaries
Signal Processing - Special section on signal processing technologies for short burst wireless communications
Spread Spectrum Systems: With Commercial Applications
Spread Spectrum Systems: With Commercial Applications
Bayesian Pursuit algorithm for sparse representation
ICASSP '09 Proceedings of the 2009 IEEE International Conference on Acoustics, Speech and Signal Processing
ICASSP '09 Proceedings of the 2009 IEEE International Conference on Acoustics, Speech and Signal Processing
A plurality of sparse representations is better than the sparsest one alone
IEEE Transactions on Information Theory
Audio signal representations for indexing in the transform domain
IEEE Transactions on Audio, Speech, and Language Processing
Sparse approximation and the pursuit of meaningful signal models with interference adaptation
IEEE Transactions on Audio, Speech, and Language Processing
Tree-Based Pursuit: Algorithm and Properties
IEEE Transactions on Signal Processing
Matching pursuit and atomic signal models based on recursive filterbanks
IEEE Transactions on Signal Processing
Fast matching pursuit with a multiscale dictionary of Gaussianchirps
IEEE Transactions on Signal Processing
Matching pursuits with time-frequency dictionaries
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Stochastic time-frequency dictionaries for matching pursuit
IEEE Transactions on Signal Processing
Dark Energy in Sparse Atomic Estimations
IEEE Transactions on Audio, Speech, and Language Processing
Union of MDCT Bases for Audio Coding
IEEE Transactions on Audio, Speech, and Language Processing
Sparse and structured decompositions of signals with the molecular matching pursuit
IEEE Transactions on Audio, Speech, and Language Processing
Sparse Linear Regression With Structured Priors and Application to Denoising of Musical Audio
IEEE Transactions on Audio, Speech, and Language Processing
On the exponential convergence of matching pursuits in quasi-incoherent dictionaries
IEEE Transactions on Information Theory
IEEE Transactions on Information Theory
On universal quantization by randomized uniform/lattice quantizers
IEEE Transactions on Information Theory - Part 2
Signal Recovery From Random Measurements Via Orthogonal Matching Pursuit
IEEE Transactions on Information Theory
Matching pursuit filters applied to face identification
IEEE Transactions on Image Processing
Low-rate and flexible image coding with redundant representations
IEEE Transactions on Image Processing
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Matching Pursuits are a class of greedy algorithms commonly used in signal processing, for solving the sparse approximation problem. They rely on an atom selection step that requires the calculation of numerous projections, which can be computationally costly for large dictionaries and burdens their competitiveness in coding applications. We propose using a non-adaptive random sequence of subdictionaries in the decomposition process, thus parsing a large dictionary in a probabilistic fashion with no additional projection cost nor parameter estimation. A theoretical modeling based on order statistics is provided, along with experimental evidence showing that the novel algorithm can be efficiently used on sparse approximation problems. An application to audio signal compression with multiscale time-frequency dictionaries is presented, along with a discussion of the complexity and practical implementations.