Abstract

Adapted waveform analysis uses a library of orthonormal bases and an efficiency functional to match a basis to a given signal or family of signals. It permits efficient compression of a variety of signals, such as sound and images. The predefined libraries of modulated waveforms include orthogonal wavelet-packets and localized trigonometric functions, and have reasonably well-controlled time-frequency localization properties. The idea is to build out of the library functions an orthonormal basis relative to which the given signal or collection of signals has the lowest information cost. The method relies heavily on the remarkable orthogonality properties of the new libraries: all expansions in a given library conserve energy and are thus comparable. Several cost functionals are useful; one of the most attractive is Shannon entropy, which has a geometric interpretation in this context.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Keywords

Orthonormal basisAlgorithmEntropy (arrow of time)OrthogonalityComputer scienceInformation theoryWaveletOrthogonal basisSignal processingSignal compressionWaveformMathematicsTheoretical computer scienceArtificial intelligenceDigital signal processing

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2006 IEEE Transactions on Information Theory 22524 citations

Publication Info

Year
1992
Type
article
Volume
38
Issue
2
Pages
713-718
Citations
3140
Access
Closed

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Cite This

Ronald R. Coifman, Mladen Victor Wickerhauser (1992). Entropy-based algorithms for best basis selection. IEEE Transactions on Information Theory , 38 (2) , 713-718. https://doi.org/10.1109/18.119732

Identifiers

DOI
10.1109/18.119732

Data Quality

Data completeness: 77%