An adaptive quasi-Newton algorithm for eigensubspace estimation
- 1 January 2000
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Signal Processing
- Vol. 48 (12), 3328-3333
- https://doi.org/10.1109/78.886996
Abstract
We derive and discuss a new adaptive quasi-Newton eigen-estimation algorithm and compare it with the RLS-type adaptive algorithms and the quasi-Newton algorithm proposed by Mathew et al. (1995) through experiments with stationary and nonstationary data.Keywords
This publication has 6 references indexed in Scilit:
- Principal component extraction using recursive least squares learningIEEE Transactions on Neural Networks, 1995
- Projection approximation subspace trackingIEEE Transactions on Signal Processing, 1995
- Adaptive estimation of eigensubspaceIEEE Transactions on Signal Processing, 1995
- Orthogonal eigensubspace estimation using neural networksIEEE Transactions on Signal Processing, 1994
- Principal component analysis by gradient descent on a constrained linear Hebbian cellPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1989
- An optimal orthonormal system for discriminant analysisPattern Recognition, 1985