双线性形式识别的RLS算法

Camelia Elisei-Iliescu, C. Paleologu, R. Dobre, S. Ciochină, J. Benesty
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引用次数: 5

摘要

双线性系统涉及许多有趣的应用,特别是与非线性系统的近似有关。在这种情况下,双线性术语通常根据输入-输出关系(即,关于数据)来定义。最近,引入了一种不同的方法,通过定义与时空模型的脉冲响应相关的双线性项,该模型类似于多输入/单输出(MISO)系统。此外,在这个框架中,已经涉及到维纳滤波器来解决这些双线性形式的识别问题。鉴于维纳滤波在实际应用中可能并不总是非常高效或方便,本文提出了一种基于递归最小二乘(RLS)算法的自适应滤波方法。在系统识别环境中进行的仿真(基于MISO系统方法)表明了该算法的吸引人的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An RLS algorithm for the identification of bilinear forms
Bilinear systems are involved in many interesting applications, especially related to the approximation of nonlinear systems. In this context, the bilinear term is usually defined in terms of an input-output relation (i.e., with respect to the data). Recently, a different approach has been introduced, by defining the bilinear term with respect to the impulse responses of a spatiotemporal model, which resembles a multiple-input/single-output (MISO) system. Also, in this framework, the Wiener filter has been involved to address the identification problem of these bilinear forms. Since the Wiener filter may not be always very efficient or convenient to use in practice, we propose in this paper an adaptive filtering approach based on the recursive least-squares (RLS) algorithm. Simulations performed in the context of system identification (based on the MISO system approach) indicate the appealing performance of this algorithm.
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