Identification of non linear system modeled in Reproducing Kernel Hilbert Space using a new criterion

N. Souilem, I. Elaissi, O. Taouali, M. Hassani
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Abstract

This paper proposes a new algorithm to estimate the required number of parameters in the models developed in Reproducing Kernel Hilbert Space (RKHS). The proposed method considers models with growing complexities and calculates for each a given matrix, such that these matrices tend to singularity. The required number of parameters is given by verifying a criterion on the determinants of these matrices.
用一种新准则辨识再现核希尔伯特空间中非线性系统
本文提出了一种新的估计核希尔伯特空间(RKHS)模型中所需参数数量的算法。该方法考虑了复杂程度不断增加的模型,并对每个给定矩阵进行计算,使得这些矩阵趋于奇点。通过验证这些矩阵的行列式的判据,可以得到所需的参数数。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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