Convergence analysis of deterministic discrete time system of a unified self-stabilizing algorithm for PCA and MCA

Unified algorithms for principal and minor components analysis can be used to extract principal components and if altered simply by the sign, it can also serve as a minor component extractor. Obviously, the convergence of these algorithms is an essential issue in practical applications. This paper s...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Neural networks 2012-12, Vol.36, p.64-72
Hauptverfasser: Kong, Xiangyu, An, Qiusheng, Ma, Hongguang, Han, Chongzhao, Zhang, Qi
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Unified algorithms for principal and minor components analysis can be used to extract principal components and if altered simply by the sign, it can also serve as a minor component extractor. Obviously, the convergence of these algorithms is an essential issue in practical applications. This paper studies the convergence of a unified PCA and MCA algorithm via a corresponding deterministic discrete-time (DDT) system and some sufficient conditions to guarantee convergence are obtained. Simulations are carried out to further illustrate the theoretical results achieved.
ISSN:0893-6080
1879-2782
DOI:10.1016/j.neunet.2012.08.016