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A Recursive Nonlinear System Identification Method Based on Binary Measurements

机译:一种基于二进制测量的递归非线性系统辨识方法

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摘要

An online approach to nonlinear system identification based on binary observations is presented in this paper. This recursive method is a nonlinear extension of the LMS-like (least-mean-squares) basic identification method using binary observations (LIMBO). It can be applied in the case of weakly nonlinear Duffing oscillator coupled with a linear system characterized by a finite impulse response. It is then possible to estimate both Duffing and impulse response coefficients knowing only the system input and the sign of the system output. The impulse response is identified up to a positive multiplicative constant. The proposed method is compared in terms of convergence speed and estimation quality with the usual LMS approach, which is not based on binary observations.
机译:本文提出了一种基于二进制观测值的非线性系统辨识在线方法。此递归方法是使用二进制观测值(LIMBO)的LMS类(最小均方)基本识别方法的非线性扩展。它可以用于弱非线性Duffing振荡器与以有限脉冲响应为特征的线性系统耦合的情况。然后可以仅知道系统输入和系统输出的符号来估计Duffing和脉冲响应系数。识别脉冲响应直至正的乘法常数。所提出的方法在收敛速度和估计质量方面与不基于二元观测的常规LMS方法进行了比较。

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