A study on data compression by dynamical system approach

Pao Yue-kong Library Electronic Theses Database

A study on data compression by dynamical system approach

 

Author: Lam, Fung-yee
Title: A study on data compression by dynamical system approach
Degree: M.Phil.
Year: 2001
Subject: Data compression (Computer science)
Hong Kong Polytechnic University -- Dissertations
Department: Dept. of Applied Mathematics
Pages: 108 leaves : ill. (some col.) ; 30 cm
Language: English
InnoPac Record: http://library.polyu.edu.hk/record=b1599538
URI: http://theses.lib.polyu.edu.hk/handle/200/1367
Abstract: The importance and demands for data compression have been increasing rapidly, especially with the growing popularity of Internet access and multimedia personal entertainment. The ratio and the quality of compression data are main concern when judging the compression algorithm. Recently, data compression techniques are dominated by the fast Fourier and wavelet transforms, which approximate the given sequence as a linear sum of the basis function, by retaining a finite number of coefficients to achieve the goal of compression. In this project, we introduce a dynamical system approach, which compresses data in a totally different way from the ones mentioned above. Taking advantage of the fact that Leaky-integrator model recurrent neural net can approximate arbitrary finite sequence, we demonstrate in this thesis how to compress UV and IR spectrum by a discrete-time recurrent neural net. As this is an initial valued problem, the information we need to store is the parameters of the system and the initial states. Compression ratio is also discussed in this thesis.

Files in this item

Files Size Format
b15995380.pdf 3.329Mb PDF
Copyright Undertaking
As a bona fide Library user, I declare that:
  1. I will abide by the rules and legal ordinances governing copyright regarding the use of the Database.
  2. I will use the Database for the purpose of my research or private study only and not for circulation or further reproduction or any other purpose.
  3. I agree to indemnify and hold the University harmless from and against any loss, damage, cost, liability or expenses arising from copyright infringement or unauthorized usage.
By downloading any item(s) listed above, you acknowledge that you have read and understood the copyright undertaking as stated above, and agree to be bound by all of its terms.

     

Quick Search

Browse

More Information