检索规则说明:AND代表“并且”;OR代表“或者”;NOT代表“不包含”;(注意必须大写,运算符两边需空一格)
检 索 范 例 :范例一: (K=图书馆学 OR K=情报学) AND A=范并思 范例二:J=计算机应用与软件 AND (U=C++ OR U=Basic) NOT M=Visual
作 者:火元莲[1] 徐天赐 齐永锋 徐玉荣 张印 HUO Yuanlian;XU Tianci;QI Yongfeng;XU Yurong;ZHANG Yin(College of Physics and Electronic Engineering,Northwest Normal University,Lanzhou 730070,China;College of Computer Science and Engineering,Northwest Normal University,Lanzhou 730070,China)
机构地区:[1]西北师范大学物理与电子工程学院,兰州730070 [2]西北师范大学计算机科学与工程学院,兰州730070
出 处:《北京邮电大学学报》2024年第1期94-99,共6页Journal of Beijing University of Posts and Telecommunications
摘 要:为了进一步提高扩散式自适应滤波算法在不同噪声环境下的性能,提出了一种新的基于P范数的变尺度扩散公平代价函数算法。该算法在公平代价函数的基础上,对误差绝对值项加入了P范数,同时利用类箕舌线函数构造了一个随误差变化的尺度因子来共同控制算法的陡峭程度,进而使算法拥有更快的收敛速度和更小的稳态误差。在高斯噪声环境以及Alpha稳定分布和伯努利-高斯分布的非高斯噪声环境中的仿真结果表明,所提算法拥有更强的鲁棒性和更低的稳态误差,在不同噪声环境下的性能均优于对比算法。A new P-norm based variable scale DFAIR diffusion fair cost function algorithm is proposed to further enhance the performance of diffusion based adaptive filtering algorithms in different noise environments.The absolute value of the error term is augmented with a P-norm and a scale factor that varies with the error is established using a tongue-like function to control the steepness of the algorithm.As a result,the convergence speed of the algorithm is accelerated and the steady-state error is reduced.The simulation results in Gaussian noise environments,as well as non-Gaussian noise environments with alpha stable distribution and Bernoulli Gaussian distribution,demonstrate the algorithm has stronger robustness and lower steady-state error.The performance of the proposed algorithm surpasses that of the comparison algorithm in various noise environments.
分 类 号:TN713[电子电信—电路与系统]
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在链接到云南高校图书馆文献保障联盟下载...
云南高校图书馆联盟文献共享服务平台 版权所有©
您的IP:3.138.61.216