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

Neural Netw. 2012 Dec:36:64-72. doi: 10.1016/j.neunet.2012.08.016. Epub 2012 Sep 17.

Abstract

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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms*
  • Computer Simulation
  • Neural Networks, Computer*
  • Principal Component Analysis*
  • Time