Robust adaptive quasi-Newton algorithms for eigensubspace estimation

IEE Proceedings: Vision, Image and Signal Processing

Volumn 150, Issue 5, 2003, Pages 321-330

  Ouyang, S ^a   Ching, P C ^b   Lee, T ^b  

^a GUILIN UNIVERSITY OF ELECTRONIC TECHNOLOGY   (China)

^b CHINESE UNIVERSITY OF HONG KONG   (Hong Kong)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; APPROXIMATION THEORY; COMPUTER SIMULATION; EIGENVALUES AND EIGENFUNCTIONS; LAGRANGE MULTIPLIERS; MATRIX ALGEBRA;

HESSIAN MATRIX; QUASI-NEWTON ALGORITHMS;

SIGNAL PROCESSING;

EID: 0344494783     PISSN: 1350245X     EISSN: None     Source Type: Journal    
DOI: 10.1049/ip-vis:20030767     Document Type: Conference Paper

References (22)

1. Schmidt, R.: 'Multiple emitter location and signal parameter estimation', IEEE Trans. Antennas Propag., 1986, 34, pp. 276-280
2. Roy, R., and Kailath, T.: 'ESPRIT-estimation of signal processing via rotational invariance techniques', IEEE Trans. Acoust. Speech Signal Process., 1989, 37, pp. 984-995
3. Comon, P., and Golub, G.H.: 'Tracking a few extreme singular values and vectors in signal processing', Proc. IEEE, 1990, 78, pp. 1327-1343
4. Golub, G.H., and Van Loan, C.F.: 'Matrix computation' (The Johns Hopkins Univ. Press, Baltimore, MD, USA, 1996, 3rd edn.)
5. DeGroat, R.D.: 'Noniterative subspace tracking', IEEE Trans. Signal Process., 1992, 40, pp. 571-577
6. Stewart, G.W.: 'An updating algorithm for subspace tracking', IEEE Trans. Signal Process., 1992, 40, pp. 1535-1541
7. Strobach, P.: 'Square-root QR inverse iteration for tracking the minor subspace', IEEE Trans. Signal Process., 2000, 48, pp. 2994-2999
8. Fu, Z.Q., and Dowling, E.M.: 'Conjugate gradient eigenstructure tracking for adaptive spectral estimation', IEEE Trans. Signal Process., 1995, 43, pp. 1151-1160
9. Kung, S.Y.: 'VLSI array processors' (Prentice-Hall, Englewood Cliffs, NJ, USA, 1988)
10. Bannour, S., and Azimi-Sadjadi, M.R.: 'Principal component extraction using recursive least squares learning', IEEE Trans. Neural Netw., 1995, 6, pp. 457-469
11. Kung, S.Y., Diamantaras, K.I., and Taur, J.S.: 'Adaptive principal component extraction (APEX) and applications', IEEE Trans. Signal Process., 1994, 42, pp. 1202-1217
12. Ouyang, S., Bao, Z., and Liao, G.S.: 'Robust recursive least squares learning algorithm for principal component analysis', IEEE Trans. Neural Netw., 2000, 11, pp. 215-221
13. Yang, B.: 'Projection approximation subspace tracking', IEEE Trans. Signal Process., 1995, 43, pp. 95-107
14. Miao, Y.F., and Hua, Y.B.: 'Fast subspace tracking and neural network learning by a novel information criterion', IEEE Trans. Signal Process., 1998, 46, pp. 1967-1979
15. Kang, Z.J., Chatterjee, C., and Roychowdhury, V.P.: 'An adaptive quasi-Newton algorithm for eigensubspace estimation', IEEE Trans. Signal Process., 2000, 48, pp. 3328-3333
16. Mathew, G., Reddy, V.U., and Dasgupta, S.: 'Adaptive estimation of eigensubspace', IEEE Trans. Signal Process., 1995, 43, pp. 401-411
17. Zhang, Q.F., and Leung, Y.W.: 'Energy function for the one-unit Oja algorithm', IEEE Trans. Neural Netw., 1995, 6, pp. 1291-1293
18. Hua, Y.B., Xiang, Y., Chen, T.P., Abed-Meraim, K., and Miao, Y.F.: 'Natural power method for fast subspace tracking'. Proc. IEEE Workshop on Neural networks for signal processing IX, Madison, USA, 1999, pp. 176-185
19. Rao, Y.N., and Principe, J.C.: 'A fast, online algorithm for PCA and its convergence characteristics'. Proc. IEEE Workshop on Neural networks for signal processing X, Sydney, Australia, 2000, vol. 1, pp. 299-307
20. Kushner, H.J., and Clark, D.S.: 'Stochastic approximation methods for constrained and unconstrained systems' (Springer-Verlag, New York, USA, 1978)
21. Oja, E.: 'Principal components, minor components, and linear neural networks', Neural Netw., 1992, 5, pp. 927-935
22. Haykin S.: 'Adaptive filter theory' (Prentice-Hall, Englewood Cliffs, NJ, USA, 1991, 2nd edn.)