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A New Parallel-by-Cell Approach to Undistorted Data Compression Based on Cellular Automaton and Genetic Algorithm

机译:基于元胞自动机和遗传算法的无失真并行数据压缩新方法

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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 compar- ison 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.
机译:提出了一种新的基于元胞自动机和遗传算法的无单元并行数据压缩方法。通过使用遗传进化算法获得了细胞自动机中的局部压缩规则。讨论了超并行压缩的正确性,时间复杂度以及相关的符号动态行为。与其他传统的顺序或小规模并行方法进行无失真数据压缩相比,所提出的方法显示出更高的实时性能,更好的适用性和适用于脉动硬件的可行性。

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