New parallel-by-cell approach to undistorted data compression based on cellular automaton and genetic algorithm

被引：1

作者：

Gu J. ^{[1
]}

Shuai D. ^{[2
]}

机构：

[1] State Key Lab. Intell. Technol. S., Tsinghua University

[2] Dept. of Comp. Sci. and Technology, E. China Univ. of Sci. and Technol.

来源：

Journal of Computer Science and Technology | 1999年 / 14卷 / 6期

关键词：

data compression; genetic algorithm; cellular automaton; parallel processing;

D O I：

10.1007/BF02951877

中图分类号：

学科分类号：

摘要：

In this paper, a new parallel-by-cell approach to the undistorted data compression based on cellular automaton and genetic algorithm is presented. The local compression rules in a cellular automaton are obtained by using a genetic evolutionary algorithm. The correctness of the hyper-parallel compression, the time complexity, and the relevant symbolic dynamic behaviour are discussed. In comparison with other traditional sequential or small-scale parallel methods for undistorted data compression, the proposed approach shows much higher real-time performance, better suitability and feasibility for the systolic hardware implementation.

引用

页码：572 / 579

页数：7

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