Stability of Oja's PCA subspace rule

Authors:
Juha Karhunen
Affiliations:
-
Venue:
Neural Computation
Year:
1994

Citing 0
Cited 3

On Stability of Oja Algorithm

RSCTC '98 Proceedings of the First International Conference on Rough Sets and Current Trends in Computing
Stability Analysis of Oja-RLS Learning Rule

Fundamenta Informaticae
The Modified Oja-RLS Algorithm, Stochastic Convergence Analysis and Application for Image Compression

Fundamenta Informaticae

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper deals with stability of Oja's symmetric algorithm forestimating the principal component subspace of the input data.Exact conditions are derived for the gain parameter on which thediscrete algorithm remains bounded. The result is extended for anonlinear version of Oja's algorithm.