Kernel-SOM Based Nonlinear System Identification and Model Running Convergence Analysis
Yu Dong-jun①; Zhen Yu-jie①; Wu Xiao-jun②; Yang Jing-yu①
①School of Computer Science and Technology, Nanjing University of Science and Technology, Nanjing 210094, China; ②School of Information Engineering, Southern Yangtse University, Wuxi 214122, China
Abstract:A Kernel-SOM based unsupervised nonlinear system identification algorithm is proposed. Analysis of the model running convergence of the proposed algorithm is performed, and the convergence theorem is proofed by considering both identification error and initial input error. Numerical simulation results demonstrate the effectiveness of the proposed identification algorithm and the correctness of the convergence theorem.