NDLI: Representations of stochastic processes using coiflet-type wavelets

Content Provider	IEEE Xplore Digital Library
Author	Dong Wei Haiguang Cheng
Copyright Year	2000
Description	Author affiliation: Dept. of Electr. & Comput. Eng., Drexel Univ., Philadelphia, PA, USA (Dong Wei)
Abstract	The wavelet series expansion requires a high computational complexity; by means of projection, the scaling coefficients are computed at the finest scale in order to realize the Mallat algorithm to compute the wavelet coefficients at coarser scales. We propose a fast and practical algorithm to approximate the wavelet series expansion. The algorithm is based on sampling and reconstruction with coiflet-type wavelets, which possess vanishing moments on both scaling function and wavelet. We evaluate the performance of the algorithm by establishing the convergence rates and asymptotic forms for the mean-square errors in the scaling coefficients and wavelet coefficients of the synthesized stochastic process.
Starting Page	549
Ending Page	553
File Size	372114
Page Count	5
File Format	PDF
ISBN	0780359887
DOI	10.1109/SSAP.2000.870185
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2000-08-16
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Stochastic processes Wavelet coefficients Convergence Telecommunication computing Sampling methods Image reconstruction Data compression Noise reduction Approximation methods Approximation error
Content Type	Text
Resource Type	Article

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Representations of stochastic processes using coiflet-type wavelets