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Matching Pursuit

Matching Pursuit with Stochastic Time-Frequency Dictionaries - software
Recent version MP5 is available at
This page contains links to software for Matching Pursuit (*) decomposition of signals in stochastic time-frequency dictionaries of Gabor functions, written by Dobiesław Ircha under supervision of Piotr J. Durka, called hereafter "the authors". Authors grant a nonexclusive license to use this software and documentation for education and research. No part of the software or documentation can be included in any commercial product without prior obtaining a written permission of the authors. This software is provided "as is" and without any express or implied warranties. We do not provide technical support.

This implementation is described in the paper Stochastic time-frequency dictionaries for Matching Pursuit, P.J. Durka, D. Ircha and K.J. Blinowska, IEEE Transactions on Signal Processing, Vol. 49, No. 3, pp. 507-510, March 2001

Before you download the software, you may try it in an interactive way here mp v.III   (relatively stable & documented)

Linux executable mp31 161k
C source code mp31_src.tgz 250k
MS Windows mp31.exe 149k
HTML manual
Java applet for interactive display of results: view online
download mpview.jar (run java -cp mpview.jar mpview)
download source code mpview_src.tgz
mp v.IV -- undocumented, sorry :(
Linux executable mp4 72k
Linux executable (static link) mp4.static.gz 194k
C source code mp4_src.tgz 219k
MS Windows mp4.exe 152k

Finally, fast and experimental mp with Voronoy search written by D. Blacha (documentation only in Polish, sorry :(.
Matlab files for reading and post-processing results of MP decompositions stored in the binary format of the above packages: zip w/routines and demo
pthread.dll, available e.g. here, is needed to run mp31.exe and mp4.exe
Matching Pursuit (MP) is an iterative algorithm for adaptive approximations, first published under this name in Matching Pursuit with time-frequency dictionaries, S. Mallat and Z. Zhang, IEEE Transactions on Signal Processing, Dec 1993--software available at Similar approach was proposed in: Signal approximation via data-adaptive normalized Gaussian function and its applications for speech processing, S. Qian, D. Chen and K. Chen, Proc. ICASSP-92, San Francisco, CA, March 23-26, 1992, pp.141-144.
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