Misadjustment Measurement with Normalized Weighted Noise Covariance based LMS Algorithm

2019 International Conference on Computer, Communication, Chemical, Materials and Electronic Engineering (IC4ME2) Pub Date : 2019-07-01 DOI:10.1109/IC4ME247184.2019.9036560

Md. Shoriful Islam, Rubaiyat Yasmin, Shihab Kaviraz, Most.Meftahul Zannat

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Abstract

In this paper, a new refined technique called Normalized Weighted Noise Covariance based LMS (NWC-LMS) technique has been proposed to measure misadjustment of an adaptive filtering system. This technique is aimed to track the measured misadjustment properly. Several techniques had been developed during past years to analyze and calculate the measured misadjustment based on weight noise covariance matrix. However there are still significant error in misadjustment measurement to the calculated misadjustment. The performance of the proposed NWC-LMS technique is verified by computer simulations for an unknown system with additive white Gaussian noise. From the simulation results it is observed that even for larger value of step size, NWC-LMS technique can predict the misadjustment better than the conventional techniques. Around 37 % error improvement is achieved for the larger step size 0.04 with same input condition with our proposed NWC-LMS technique.

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基于归一化加权噪声协方差LMS算法的失调测量

本文提出了一种新的改进技术——基于归一化加权噪声协方差的LMS (NWC-LMS)技术来测量自适应滤波系统的失调。该技术的目的是正确跟踪测量误差。近年来发展了几种基于权值噪声协方差矩阵的测量误差分析和计算技术。然而，对计算出的误差差进行测量时仍存在较大误差。通过对具有加性高斯白噪声的未知系统的计算机仿真，验证了所提出的NWC-LMS技术的性能。仿真结果表明，当步长较大时，NWC-LMS技术也能较好地预测误差。在相同的输入条件下，对于较大的步长0.04，我们提出的NWC-LMS技术实现了约37%的误差改进。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2019 International Conference on Computer, Communication, Chemical, Materials and Electronic Engineering (IC4ME2)

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