A study on an estimation system of inverse transfer function using adaptive filter estimating minimum‐phase and allpass transfer function

Masaki Kobayashi, Y. Itoh, J. Okello
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Abstract

A structure is proposed for an adaptive system with an adaptive filter located before the unknown system (pre-inverse adaptive system) for estimation of the inverse of the transfer function (inverse transfer function) of the unknown system. In general, when an adaptive transversal filter is used as an adaptive filter, the delay signal of the output of the unknown system is needed in the adaptive algorithm for the weights. Since an adaptive filter is inserted in the front stage, this signal cannot be observed, so that a replica of the unknown system is needed. In this paper, an adaptive system that does not require this replica is discussed. Estimation of the inverse transfer function of the minimum phase of the unknown system is performed by an adaptive exponential filter and an inverse copy of the weights of the exponential filter placed in front of the unknown system. The signal within the adaptive algorithm consists of the observable input signal to the adaptive exponential filter and the estimation error. Estimation of the inverse transfer function for the allpass transfer function of the unknown system is performed by the adaptive transversal filter and the reversing copy of the weight to the transversal filter located before the unknown system. The signal in the adaptive system consists of the observable input signal to the exponential filter and the estimation error. Convergence of the weight is studied from the point of view of monotonic increase of the gradient. The unique feature of the approach is that the algorithm of the two adaptive filters consists of a gradient algorithm with guaranteed convergence for the weights and of copies of the weights after updating. Finally, a performance evaluation of the adaptive system and a comparison with conventional systems are performed by numerical simulation. © 2007 Wiley Periodicals, Inc. Electron Comm Jpn Pt 3, 90(9): 10– 17, 2007; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ecjc.20305
利用自适应滤波器估计最小相位和全通传递函数的逆传递函数估计系统的研究
提出了一种自适应系统的结构,在未知系统(预逆自适应系统)前设置自适应滤波器,用于估计未知系统的传递函数逆(逆传递函数)。一般情况下,当采用自适应横向滤波器作为自适应滤波器时,在自适应算法中需要未知系统输出的延迟信号作为权重。由于在前级插入了自适应滤波器,因此无法观察到该信号,因此需要未知系统的副本。本文讨论了一种不需要复制的自适应系统。通过自适应指数滤波器和放置在未知系统前面的指数滤波器权值的逆拷贝来估计未知系统最小相位的逆传递函数。自适应算法中的信号由自适应指数滤波器的可观测输入信号和估计误差组成。通过自适应横向滤波器对未知系统的全通传递函数进行逆传递函数估计,并将权值反向复制到未知系统前的横向滤波器上。自适应系统中的信号由指数滤波器的可观测输入信号和估计误差组成。从梯度单调递增的角度研究了权值的收敛性。该方法的独特之处在于两个自适应滤波器的算法由保证权值收敛的梯度算法和更新后的权值副本算法组成。最后,通过数值仿真对自适应系统进行了性能评价,并与传统系统进行了比较。©2007 Wiley期刊公司电子工程学报,2009,35 (6):1145 - 1145;在线发表于Wiley InterScience (www.interscience.wiley.com)。DOI 10.1002 / ecjc.20305
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