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Author Bieleck, Tomasz ♦ Song, Li M. ♦ Yau, Stephen S. T. ♦ Kwong, Man Kam
Source CiteSeerX
Content type Text
File Format PDF
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Random Wavelet Transforms ♦ Algebraic Geometric Coding ♦ Signal Compression ♦ Fractional Noise ♦ Discrete Random Wavelet Transforms ♦ Potential Application ♦ Many Aspect ♦ New Algorithm ♦ Detailed Survey ♦ Ensuing Data ♦ Classical Counterpart ♦ Main Idea ♦ Classical Wavelet-based Algorithm ♦ Simultaneous Compression
Abstract The concepts of random wavelet transforms and discrete random wavelet transforms are introduced. It is shown that these transforms can lead to simultaneous compression and de-noising of signals that have been corrupted with fractional noises. Potential applications of algebraic geometric coding theory to encode the ensuing data are also discussed. Introduction In this paper, we first outline the main ideas behind classical wavelet-based algorithms of compression and de-noising of signals. We then introduce the concept of random wavelet transforms and discrete random wavelet transforms, which are more effective than their classical counterparts in handling fractional noises. Finally, we discuss potential applications of the method of algebraic geometric coding of data produced by our new algorithms. Since this article is not a detailed survey, many aspects of both compression and coding algorithms will not be presented here. For example, we do not discuss thresholding algorithms; we ...
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research
Education Level UG and PG ♦ Career/Technical Study
Learning Resource Type Article