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Open AccessJournal ArticleDOI

Efficient coding of natural sounds.

Michael S. Lewicki
- 01 Apr 2002 - 
- Vol. 5, Iss: 4, pp 356-363
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TLDR
It is reported that several basic auditory nerve fiber tuning properties can be accounted for by adapting a population of filter shapes to encode natural sounds efficiently.
Abstract
The auditory system encodes sound by decomposing the amplitude signal arriving at the ear into multiple frequency bands whose center frequencies and bandwidths are approximately exponential functions of the distance from the stapes. This organization is thought to result from the adaptation of cochlear mechanisms to the animal's auditory environment. Here we report that several basic auditory nerve fiber tuning properties can be accounted for by adapting a population of filter shapes to encode natural sounds efficiently. The form of the code depends on sound class, resembling a Fourier transformation when optimized for animal vocalizations and a wavelet transformation when optimized for non-biological environmental sounds. Only for the combined set does the optimal code follow scaling characteristics of physiological data. These results suggest that auditory nerve fibers encode a broad set of natural sounds in a manner consistent with information theoretic principles.

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References
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Journal ArticleDOI

A theory for multiresolution signal decomposition: the wavelet representation

TL;DR: In this paper, it is shown that the difference of information between the approximation of a signal at the resolutions 2/sup j+1/ and 2 /sup j/ (where j is an integer) can be extracted by decomposing this signal on a wavelet orthonormal basis of L/sup 2/(R/sup n/), the vector space of measurable, square-integrable n-dimensional functions.
Book

A wavelet tour of signal processing

TL;DR: An introduction to a Transient World and an Approximation Tour of Wavelet Packet and Local Cosine Bases.
Journal ArticleDOI

Ten Lectures on Wavelets

TL;DR: In this article, the regularity of compactly supported wavelets and symmetry of wavelet bases are discussed. But the authors focus on the orthonormal bases of wavelets, rather than the continuous wavelet transform.
Journal ArticleDOI

Atomic Decomposition by Basis Pursuit

TL;DR: Basis Pursuit (BP) is a principle for decomposing a signal into an "optimal" superposition of dictionary elements, where optimal means having the smallest l1 norm of coefficients among all such decompositions.
Journal ArticleDOI

An information-maximization approach to blind separation and blind deconvolution

TL;DR: It is suggested that information maximization provides a unifying framework for problems in "blind" signal processing and dependencies of information transfer on time delays are derived.
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