Crosscumulants Based Approaches for the Structure Identification of Volterra Models

作     者：Houda Mathlouthi Kamel Abederrahim Faouzi Msahli Gerard Favier 

作者机构：National School of Engineers of Gabes Route de Medenine 6029 Gabes National School of Engineers of Monastir Avenue Ibn Jazzar 5019 Monastir I3S Laboratory UNSA/CNRS 2000 Route des Lucioles Batiment Algorithmes Euclide Sophia-Antipolis Biot 

出 版 物：《International Journal of Automation and computing》 (国际自动化与计算杂志（英文版）)

年 卷 期：2009年第6卷第4期

页      面：420-430页

核心收录：

学科分类：0711[理学-系统科学] 07[理学] 08[工学] 070105[理学-运筹学与控制论] 081101[工学-控制理论与控制工程] 071101[理学-系统理论] 0811[工学-控制科学与工程] 0701[理学-数学] 

主　　题：Structure identification Volterra model crosscumulants Caussian input symmetric input 

摘      要：In this paper, we address the problem of structure identification of Volterra models. It consists in estimating the model order and the memory length of each kernel. Two methods based on input-output crosscumulants are developed. The first one uses zero mean independent and identically distributed Caussian input, and the second one concerns a symmetric input sequence. Simulations are performed on six models having different orders and kernel memory lengths to demonstrate the advantages of the proposed methods.