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Stephane G. Mallat

Associate Professor of Computer Science
Ph.D, University of Pennsylvania

Professor Mallat works in applied mathematics for signal and information processing, as well as in computer vision. He made some fundamental contributions to the development of the wavelet theory and its applications to the characterization of transients in sounds and images. The analysis of complex signals often requires computing adaptive decompositions over feature vectors that are selected to match the local signal structures. Professor Mallat studies the underlying non-linear approximation theory issues and has developed algorithms for music synthesis and image segmentation in particular. He is currently investigating a characterization of locally stationary processes and robust procedures to estimate the variations of the local spectrum in speech and seismic recordings.

  1. S. Mallat, (1989). ``A Theory for Multiresolution Signal Decomposition: the Wavelet Representation,'' IEEE Transactions on Pattern Analysis and Machine Intelligence, 11:674--693.

  2. S. Mallat, W.L. Hwang, (1992). ``Singularity Detection and Processing with Wavelets,'' IEEE Transactions on Information Theory, 32(2).

  3. S. Mallat, Z. Zhang, (1993). ``Matching Pursuits with Time-Frequency Dictionaries,'' IEEE Transactions on Signal Processing, 41(12):3397--3415.