混沌蚁群组合优化算法实现盲信号检测

Blind signals detection with chaos ant colony optimization algorithm

根据混沌映射的伪随机性、遍历性以及规律性等特点提出一种新的算法,基于混沌-蚁群组合优化盲检测算法,即在信息素初始化时采用混沌初始化,并且在信息素更新时加入混沌扰动。仿真实验分别采用了4种不同的混沌映射:经典的Logistic映射、两种阶数不同的切比雪夫映射和改进的H映射。仿真结果表明,提出的基于混沌蚁群组合优化盲检测算法(CACO)可以提高计算效率,表现出了优于文献算法的良好性能。

According to the pseudo-random chaotic map,such as quasi-random and regularity the characteristics of the chaos algorithm,this paper gives a new algorithm,called chaos ant colony optimization algorithm,which is used to initialize pheromone chaotic initialization and updated when pheromone chaotic disturbance.Furthermore,the paper applies this new algorithm to blind identification.The simulations use four different chaotic mapping：The classic Logistic mapping;Chebyshev mapping and the improved H mapping.The simulation results show that the proposed algorithm which based on chaos-ant colony optimization-blind detection algorithm（CACO）,increases computational efficiency,and is more superior to the literature to show the good performance of algorithm.