离散非线性系统Worst-Case辨识——小波逼近法
THE WORST-CASE IDENTIFICATION OF DISCREET TIME NONLINEAR SYSTEMS:A WAVELET APPROXIMATION APPROACH
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摘要: 利用小波逼近的软阈（Soft-Thresholding）方法，研究了离散非线性系统的Worst-Case辨识问题．证明了该算法在Worst-Case误差下的拟最优性和光滑性；估计了该算法的Worst-Case误差：给出了存在鲁棒收敛的辨识算法的充要条件；最后，证明了小波网逼近算法是鲁棒收敛的．Abstract: In this paper the problem of robust identification of nonlinear discrete-time systems via wavelet networks is studied. An identification algorithm is proposed. It is shown that the algorithm has the properties of smoothness and near-minimaxity. In addition, for some input, the necessary and sufficient condition on the existence of a robustly convergent identification algorithm is given. With that the wavelet approximation algorithm is shown to be robustly convergent.
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