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首页> 外文期刊>Electronics and Communications in Japan. Part 3, Fundamental Electronic Science >A Study on an Estimation System of Inverse Transfer Function Using Adaptive Filter Estimating Minimum-Phase and Allpass Transfer Function
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A Study on an Estimation System of Inverse Transfer Function Using Adaptive Filter Estimating Minimum-Phase and Allpass Transfer Function

机译：利用最小相位和全通传递函数的自适应滤波器估计逆传递函数的估计系统的研究

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摘要

A structure is proposed for an adaptive system with an adaptive filter located before the unknown system (preinverse 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.
机译：提出了一种具有自适应滤波器的自适应系统的结构，该自适应滤波器位于未知系统（逆前自适应系统）之前，用于估计未知系统的传递函数的逆（逆传递函数）。通常，当将自适应横向滤波器用作自适应滤波器时，在用于权重的自适应算法中需要未知系统的输出的延迟信号。由于自适应滤波器插入前级，因此无法观察到该信号，因此需要未知系统的副本。在本文中，讨论了不需要此副本的自适应系统。未知系统最小相位的逆传递函数的估计是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重的反副本来执行的。自适应算法中的信号由自适应指数滤波器的可观察输入信号和估计误差组成。未知系统的全通传递函数的逆传递函数的估计由自适应横向滤波器和权重的逆向副本传递给位于未知系统之前的横向滤波器执行。自适应系统中的信号由到指数滤波器的可观察输入信号和估计误差组成。从梯度的单调增加的角度研究权重的收敛。该方法的独特之处在于，两个自适应滤波器的算法由梯度算法组成，该梯度算法可保证权重和更新后权重副本的收敛性。最后，通过数值模拟对自适应系统进行性能评估并与常规系统进行比较。

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