计算机科学

计算机科学 ›› 2020, Vol. 47 ›› Issue (6): 242-246.doi: 10.11896/jsjkx.190500080

• 计算机网络 • 上一篇    下一篇

扩散式最大相关熵准则变步长仿射投影符号算法

林云, 黄桢航, 高凡   

  1. 重庆邮电大学通信与信息工程学院 重庆 400065
  • 收稿日期:2019-05-16 出版日期:2020-06-15 发布日期:2020-06-10
  • 通讯作者: 黄桢航(zhenhanghuang@foxmail.com)
  • 作者简介:lycqupt@sina.com

Diffusion Maximum Correntropy Criterion Variable Step-size Affine Projection Sign Algorithm

LIN Yun, HUANG Zhen-hang, GAO Fan   

  1. College of Communication and Information Engineering,Chongqing University ofPosts and Telecommunications,Chongqing 400065,China
  • Received:2019-05-16 Online:2020-06-15 Published:2020-06-10
  • About author:LIN Yun,Ph.D,associate professor,postgraduate supervisor.His main research interests include adaptive filtering and compression sensing filtering.
    HUANG Zhen-hang,postgraduate.His main research interests include adaptive filtering,distributed adaptive filtering.

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摘要： 目前大多数分布式估计算法以最小均方误差准则作为代价函数,在脉冲噪声下性能恶化乃至发散。扩散式仿射投影符号算法(Diffusion Affine Projection Sign Algorithm,DAPSA)以L1范数为代价函数,在脉冲噪声环境中具有良好的鲁棒性,并且具有较快的收敛速度。然而,固定步长的DAPSA在保持较大的初始收敛速度和较低的稳态误差之间存在矛盾。为降低非高斯噪声环境下DAPSA的稳态误差,同时仍保持较快的初始收敛速度,文中提出了一种扩散式最大相关熵准则变步长仿射投影符号算法(Diffusion Maximum Correntropy Criterion Variable StepSize Affine Projection Sign Algorithm,DMCCVSS-APSA)。首先,该算法利用改进的卡方核作为核函数,自适应更新算法每次迭代过程中的步长取值,在取得较快初始收敛速度的同时可有效降低稳态误差;然后,提出了一种基于系统先验误差的自适应动态范围方法,以进一步降低稳态误差;最后,通过改进卡方核与改进高斯核函数的对比实验,DMCCVSS-APSA与其他分布式算法的对比实验、不同脉冲噪声环境下DMCCVSS-APSA和DAPSA的对比实验,验证了所提算法的性能表现。仿真结果表明,DMCCVSS-APSA与对比算法相比表现良好,在相似的初始收敛速度下稳态误差降低了5dB以上。实验数据充分说明,在固定步长的DAPSA的基础上提出的变步长方法和自适应动态范围方法,具有对脉冲噪声的强鲁棒性的同时,能有效降低稳态误差,提升了分布式仿射投影类算法的性能表现。最后指出所提算法在ATC式联合方式和最优灵敏度的取值上需要进一步的研究。

关键词: 冲击噪声, 分布式自适应估计, 卡方核, 扩散式, 最大相关熵

Abstract: At present,most distributed estimation algorithms minimize mean square error as a cost function,which willarise the performance deteriorates or even diverge under the impulsive noises.The diffusion affine projection sign algorithm (DAPSA) uses L1 norm as cost function,which is robustness to impulsive noises environment,and has a fast convergence speed.However,there is a contradiction between maintaining a large initial convergence speed and a low steady-state erro under a fixed step-size.In order to reduce the steady-state adjustment of DAPSA in a non-Gaussian noise environment while maintaining a fast initial convergence speed,a diffusion maximum correntropy criterion variable step size affine projection sign algorithm (DMCCVSS-APSA) is proposed.Firstly,the algorithm uses the improved chi-square kernel instead of improved gaussian kernel as the kernel function.The adaptive step size method can effectively reduce the steady-state error while achieving the faster initial convergence speed.The adaptive dynamic range method based on a priori error estimation can further reduce the steady-state error.Then the improved chi-square kernel is compared with the improved gaussian kernel,the DMCCVSS-APSA is compared with other distributed algorithms and the DMCCVSS-APSA is compared with DAPSA under different impulsive noises.Experiments verify the performance of the proposed algorithm.Simulation results show that DMCCVSS-APSA performs better than the contrast algorithms,and the steady-state error is reduced more than 5 dB at a similar initial convergence speed.The experimental data fully demonstrates that the variable step size method and the adaptive dynamic range method based on fixed step-size DAPSA can effectively reduce the steady-state error and have strong robustness to impulsive noises.It is an optimization of the distributed affine projection algorithm.Finally,the proposed algorithm needs further research on the combination of ATC mode and the optimal sensitivity factor.

Key words: Chi-square kernel, Diffusion, Distributed adaptive estimation, Impulsive noises, Maximum correntropy criterion

中图分类号: 

  • TN911.7
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[1] 林云, 黄桢航, 高凡.
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计算机科学, 2021, 48(5): 263-269. https://doi.org/10.11896/jsjkx.200300043
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