Stability and chaos of LMSER PCA learning algorithm

Jian Cheng Lv and Zhang Yi

Chaos, Solitons & Fractals, 2007, vol. 32, issue 4, 1440-1447

Abstract: LMSER PCA algorithm is a principal components analysis algorithm. It is used to extract principal components on-line from input data. The algorithm has both stability and chaotic dynamic behavior under some conditions. This paper studies the local stability of the LMSER PCA algorithm via a corresponding deterministic discrete time system. Conditions for local stability are derived. The paper also explores the chaotic behavior of this algorithm. It shows that the LMSER PCA algorithm can produce chaos. Waveform plots, Lyapunov exponents and bifurcation diagrams are presented to illustrate the existence of chaotic behavior of this algorithm.

Date: 2007
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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:32:y:2007:i:4:p:1440-1447

DOI: 10.1016/j.chaos.2005.11.076

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