A Self-Stabilizing Neural Algorithm for Total Least Squares Filtering

Kong Xiang-yu; Hu Chang-hua; Han Chong-zhao

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A Self-Stabilizing Neural Algorithm for Total Least Squares Filtering

机译：最小二乘滤波的自稳定神经算法

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摘要

A neural approach for solving the total least square (TLS) problem is presented in the paper. It is based on a linear neuron with a self-stabilizing neural algorithm, capable of resolving the TLS problem present in the parameter estimation of an adaptive FIR filters for system identification, where noisy errors affect not only the observation vector but also the data matrix. The learning rule is analyzed mathematically and the condition to guarantee the stability of algorithm is educed. The computer simulations are given to illustrate that the neural approach is self-stabilizing and considerably outperforms the existing TLS methods when a larger learning factor is used or the signal-noise-rate is lower.

机译：本文提出了一种用于解决总最小二乘（TLS）问题的神经方法。它基于具有自稳定神经算法的线性神经元，能够解决用于系统识别的自适应FIR滤波器的参数估计中存在的TLS问题，其中噪声误差不仅会影响观察向量，还会影响数据矩阵。对学习规则进行数学分析，得出保证算法稳定性的条件。给出的计算机仿真结果表明，当使用较大的学习因子或较低的信噪比时，神经方法是自稳定的，并且明显优于现有的TLS方法。

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来源
《Neural processing letters》 |2009年第3期|257-271|共15页
作者
Kong Xiang-yu; Hu Chang-hua; Han Chong-zhao;
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作者单位

The Research Institute of High Technology, 710025 Xi'an, Shaanxi, China;

The Research Institute of High Technology, 710025 Xi'an, Shaanxi, China;

School of Electronics and Information Engineering, Xi'an Jiaotong University, 710049 Xi'an, Shaanxi, China;

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原文格式 PDF
正文语种 eng
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关键词
total least square filtering; FIR filters; linear system identification; adaptive algorithm;

机译：总最小二乘滤波;FIR滤波器线性系统识别;自适应算法;

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专利

1. Fast Approximate Inverse Power Iteration Algorithm for Adaptive Total Least-Squares FIR Filtering [J] . Feng D.-Z., Zheng W.X. IEEE Transactions on Signal Processing . 2006,第期

机译：自适应总最小二乘FIR滤波的快速近似逆功率迭代算法
2. Modified gradient algorithm for total least square filtering [J] . Xiangyu Kong, Chongzhao Han, Ruixuan Wei Neurocomputing . 2006,第1a3期

机译：总最小二乘滤波的改进梯度算法
3. A Fast Recursive Total Least Squares Algorithm for Adaptive IIR Filtering [J] . Dong-Xia Chang, Da-Zheng Feng, Wei-Xing Zheng, IEEE Transactions on Signal Processing . 2005,第3期

机译：自适应IIR滤波的快速递归总最小二乘算法
4. A simple neural learning algorithm for total least-squares adaptive filtering [C] . Gao, K., Ahmad, . 1994

机译：用于总最小二乘自适应滤波的简单神经学习算法
5. Adaptive total least squares filtering. [D] . Dunne, Bruce Edward. 2003

机译：自适应总最小二乘滤波。
6. Fast Algorithms for Structured Least Squares and Total Least Squares Problems [O] . Anoop Kalsi, Dianne P. O’Leary 2006

机译：结构化最小二乘和总最小二乘问题的快速算法
7. The generalized frequency-domain adaptive filtering algorithm as an approximation of the block recursive least-squares algorithm [O] . Martin Schneider, Walter Kellermann 2016

机译：广义频域自适应滤波算法作为块递归最小二乘算法的近似

A Self-Stabilizing Neural Algorithm for Total Least Squares Filtering

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