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Convergence Analysis of a Self-Stabilizing Algorithm for Minor Component Analysis

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摘要 The M?ller algorithm is a self-stabilizing minor component analysis algorithm.This research document involves the study of the convergence and dynamic characteristics of the M?ller algorithm using the deterministic discrete time(DDT)methodology.Unlike other analysis methodologies,the DDT methodology is capable of serving the distinct time characteristic and having no constraint conditions.Through analyzing the dynamic characteristics of the weight vector,several convergence conditions are drawn,which are beneficial for its application.The performing computer simulations and real applications demonstrate the correctness of the analysis’s conclusions.
出处 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2020年第6期1585-1592,共8页 自动化学报(英文版)
基金 supported by the National Natural Science Foundation of China(61903375,61673387,61374120) Shaanxi Province Natural Science Foundation(2016JM6015)。
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