摘要
给出了计算线性分组码最小距离的遗传优化算法．该算法具有高速并行的运算速度和较强的启发式搜索能力，能较快地计算出分组码的最小距离．模拟计算表明，与模拟退火算法相比，遗传算法的计算性能更好．给出了计算线性分组码最小距离的遗传优化算法．该算法具有高速并行的运算速度和较强的启发式搜索能力，能较快地计算出分组码的最小距离．模拟计算表明，与模拟退火算法相比，遗传算法的计算性能更好．
A new method based on Genetic Algorithm is presented to compute the minimum distance of linear block codes, which is a stochastic parallel optimization algorithm for simulating natural genetics and Darwinian evolution. This method can easily be implemented on parallel computer architectures and used to find the global optimal solution of the objective function. Computer simulations are given to indicate that Genetic Algorithm is very powerful in providing good upper bounds to the minimum distance of general linear block codes.
出处
《西安电子科技大学学报》
EI
CAS
CSCD
北大核心
1999年第5期537-540,557,共5页
Journal of Xidian University
基金
军事电子预研基金
关键词
线性分组码
最小距离
遗传算法
纠错编码
linear block codes
minimum distance
genetic algorithm
performance
