【作者】 岳克强； 赵知劲； 尚俊娜；

【Author】 YUE Ke-qiang~1,ZHAO Zhi-jin~(1,2),SHANG Jun-na~(1,2) (1.Telecommunication School,Hangzhou Dianzi University,Zhejian 310018,China 2.State key lab of information control technology in communication system of No.36 Research Institute,China Electronic Technology Corporation,Jiaxing 314001,China)

【机构】 杭州电子科技大学通信工程学院； 中国电子集团第36研究所通信系统信息控制技术国家级重点实验室；

【摘要】 本文推导出了一种更有效的盲均衡准则,利用更多优秀的青蛙个体信息用于搜索更新,利用小生境的竞争策略优化青蛙个体,利用拉伸技术细化最优解附近的搜索空间避免算法早熟,以改进蛙跳算法,并将其应用于盲均衡,提出了两种新的基于改进蛙跳算法的盲均衡算法。计算机仿真结果表明,所提出的算法收敛快,稳态性能好。更多还原

【Abstract】 A more effective criterion using normalized cumulant for blind equalization algorithm is proved and introduced.In shuffled frog leaping algorithm(SFLA),more outstanding individual frog information is used to search and update,then niche competitive strategies are used to optimize the individual frog,and stretching technology is introduced to extend the search space of the optimal solution in order to avoid"premature"and to improve the algorithm’s ability of searching for a global optimum.The modified algorithms are applied in blind equalization,then two novel blind equalization algorithms based on improved SFLA are proposed.The simulation results show that the proposed algorithms have faster convergence rate and better steady-state performance.更多还原