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wavelet
(redirected from Wavelet analysis)

   Also found in: Dictionary/thesaurus, Wikipedia 0.01 sec.
wavelet
See Google Wave and wavelet compression.
wavelet [′wāv·lət]
(mathematics)
One of a collection of mathematical functions that serve as the elementary building blocks of a mathematical tool for analyzing and synthesizing functions, and for forming representations of signals in both time and frequency.

(mathematics)wavelet - A waveform that is bounded in both frequency and duration. Wavelet tranforms provide an alternative to more traditional Fourier transforms used for analysing waveforms, e.g. sound.

The Fourier transform converts a signal into a continuous series of sine waves, each of which is of constant frequency and amplitude and of infinite duration. In contrast, most real-world signals (such as music or images) have a finite duration and abrupt changes in frequency.

Wavelet transforms convert a signal into a series of wavelets. In theory, signals processed by the wavelet transform can be stored more efficiently than ones processed by Fourier transform. Wavelets can also be constructed with rough edges, to better approximate real-world signals.

For example, the United States Federal Bureau of Investigation found that Fourier transforms proved inefficient for approximating the whorls of fingerprints but a wavelet transform resulted in crisper reconstructed images.

SBG Austria.

["Ten Lectures on Wavelets", Ingrid Daubechies].


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Then they describe possible applications, among them freeway incident detection, a neuro-fuzzy logic model for estimating work-zone capacity, the wavelet analysis of traffic flow time series, the nonlinear system identification of high-rising building structures, and damage detection and health monitoring structures.
Besides the statistic methods, neural network and wavelet analysis have also been adopted in this field.
 
 
 
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