ENTROPY-BASED ALGORITHMS FOR BEST BASIS SELECTION
ENTROPY-BASED ALGORITHMS FOR BEST BASIS SELECTION
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DOI：
10.1109/18.119732
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发表时间：
1992-03-01
影响因子：
2.5
通讯作者：
WICKERHAUSER, MV
中科院分区：
文献类型：
--
作者：
COIFMAN, RR;WICKERHAUSER, MV
自适应波形分析使用正交基库和效率函数来将基与给定信号或信号族相匹配。 它允许有效压缩各种信号，例如声音和图像。 调制波形的预定义库包括正交小波包和局域三角函数，具有相当良好控制的时频局域特性。 这个想法是从库函数中构建一个正交基，相对于给定信号或信号集合具有最低的信息成本。 该方法在很大程度上依赖于新库显着的正交性特性：给定库中的所有扩展都保存能量，因此具有可比性。 有几个成本函数很有用；其中最有吸引力的一个是香农熵，它在这方面有几何解释。
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, 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, hence are comparable. Several cost functionals are useful; one of the most attractive is Shannon entropy, which has a geometric interpretation in this context.