摘要
基本蚁群优化算法在信号的盲均衡处理中存在收敛速度慢、容易陷入局部最小的缺点。为了解决基本蚁群算法所存在的不足,文是通过修正基本蚁群算法的转移概率公式给出一种改进的蚁群优化盲均衡算法,建立了基于改进蚁群优化算法的SIMO系统盲检测模型,并对基于基本蚁群优化盲均衡算法和改进蚁群优化的盲均衡算法性能进行仿真。仿真分析结果表明,文中提出的改进算法能很好地恢复出未知的发送信号,同时提高了计算效率和加快了收敛速度,表现出了优于文献算法的良好性能。
The basic ant colony optimization algorithm for the blind signal processing exits the shortcoming of slow convergence and easily falls into local minimum.To solve this problem,improved ant colony optimization algorithm is proposed by modifying the transition probability formula and SIMO system blind on detection model based on improving ant colony optimization algorithm is established,and simulate the performance of the basic and improved colony optimization blind equalization algorithm.The researched results show that the improved algorithm can be good to restore the unknown sent signals,improves computational efficiency and accelerates the convergence rate.It shows better performance than the literature algorithm.
出处
《计算机技术与发展》
2012年第4期141-143,共3页
Computer Technology and Development
基金
国家自然科学基金(60772060)
关键词
蚁群算法
盲均衡
盲检测
improved ant colony algorithm
blind equalization
blind detection
