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． The Worst-Case identification problem of discrete nonlinear systems is studied by the soft-thresholding method using wavelet approximation. The Worst-Case error of this algorithm is estimated. The necessary and sufficient conditions for the existence of robust convergence identification algorithm are given. Finally, it is proved that the wavelet network The approximation algorithm is robustly convergent.