论文部分内容阅读
针对小波盲均衡算法收敛速度较慢、稳态误差较大,易陷入局部最优解的缺点,提出了一种基于禁忌搜索策略的自适应双链DNA遗传优化小波盲均衡算法。将DNA种群初始化为双链的形式,进而选择出适应度值大的单链DNA序列作为种群个体的代表链;在交叉操作过程中,将禁忌搜索策略引入到交叉操作中,避免了迂回搜索,保证了对不同有效路径的搜索,跳出了局部最优;采用动态交叉概率提高了收敛速度,克服了DNA遗传算法早熟收敛的缺点。仿真结果表明:该算法具有更快的收敛速度和更低的均方误差。
Aiming at the disadvantage of wavelet blind equalization algorithm, such as slow convergence rate, large steady-state error and easy fall into local optimal solution, an adaptive double-stranded DNA genetic optimization wavelet blind equalization algorithm based on tabu search strategy is proposed. The DNA population is initialized into a double-stranded form, and then a single-stranded DNA sequence with a large fitness value is selected as a representative strand of a population individual. In a crossover operation, a taboo search strategy is introduced into a crossover operation to avoid roundabout search, Which ensures that the search for different effective paths jumps out of the local optimum. The dynamic crossover probability improves the convergence speed and overcomes the shortcomings of DNA genetic algorithm premature convergence. Simulation results show that the proposed algorithm has faster convergence speed and lower mean square error.