1 July 1994 Adaptive time-frequency decompositions
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Computing the optimal expansion of a signal in a redundant dictionary of waveforms is an NP-hard problem. We introduce a greedy algorithm, called a matching pursuit, which computes a suboptimal expansion. The dictionary waveforms that best match a signal's structures are chosen iteratively. An orthogonalized version of the matching pursuit is also developed. Matching pursuits are general procedures for computing adaptive signal representations. With a dictionary of Gabor functions, a matching pursuit defines an adaptive time-frequency transform. Matching pursuits are chaotic maps whose attractors define a generic noise with respect to the dictionary. We derive an algorithm that isolates the coherent structures of a signal and describe an application to pattern extraction from noisy signals.
Geoffrey M. Davis, Geoffrey M. Davis, Stephane G. Mallat, Stephane G. Mallat, Zhifeng Zhang, Zhifeng Zhang, } "Adaptive time-frequency decompositions," Optical Engineering 33(7), (1 July 1994). https://doi.org/10.1117/12.173207 . Submission:

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