摘要
提出细胞自动机元胞级超并行无失真数据压缩方法，并用遗传进化算法获得细胞自动机中的数据压缩规则。证明了细胞自动机文本压缩规则的正确性，讨论了有关的时间复杂性及符号动力学特性。与其他传统的串行或小规模并行的数据压缩方法相比，本文的方法有更好的实时性，普适性，以及Ｓｙｓｔｏｌｉｃ硬件实现的可行性。
This paper presents a new approach to the undistorted data compression, which is featured with the parallel by cell compression and the genetic algorithm (GA) guided reles for cellular automaton. The correctness of the data compression reles for cellular automaton, the computing complexity, and the relevant symbolic dynamic behaviour are discussed. In comparison with other traditional sequential or small scale parallel methods for data compression, the method proposed here has much higher real time performance, more suitability, and better feasibility for the systolic hardware implementation.
出处
《华东理工大学学报（自然科学版）》
CAS
CSCD
北大核心
1999年第2期188-193,共6页
Journal of East China University of Science and Technology
基金
国家自然科学基金
清华大学智能技术和系统国家重点实验室资助
关键词
数据压缩
遗传算法
细胞自动机
并行处理
data compression
genetic algorithm
cellular automaton
chromosome
parallel processing
