Automatic generation of RBF networks using wavelets

Pattern Recognition

Volumn 29, Issue 8, 1996, Pages 1369-1383

  Mukherjee, Shayan ^a   Nayar, Shree K ^a,b  

^a Fu Foundation School of Engineering and Applied Science   (United States)

^b HITACHI LTD   (Japan)

Author keywords

3D object recognition; Multivariate approximation; Pose estimation; Radial basis function networks; Supervised learning; Wavelets

Indexed keywords

FUNCTIONS; LEARNING SYSTEMS; MATHEMATICAL TECHNIQUES; PATTERN RECOGNITION;

MULTIVARIATE APPROXIMATION; POSE EVALUATION; WAVELETS;

NEURAL NETWORKS;

EID: 0030215647     PISSN: 00313203     EISSN: None     Source Type: Journal    
DOI: 10.1016/0031-3203(95)00164-6     Document Type: Article

References (19)

1. T. Poggio and F. Girosi, Networks for approximation and learning, Proc. IEEE 78, 1481-1497 (1990).
2. P. Baldi, Computing with arrays of bell-shaped and sigmoidal functions, Advances in Neural Information Processing Systems, R. P. Lippman, J. E. Moody and D. S. Touretzky (eds), pp. 735-742, Morgan Kaufman San Mateo, CA (1991).
3. T. Poggio and S. Edelman, A network that learns to recognize three-dimensional objects. Nature 343, 263-266 (1990).
4. J. M. Hutchinson, A. W. Lo and T. Poggio, A non-parametric approach to pricing and hedging derivative Securities via learning networks, J. Finance XLIX, 851-889 (July 1994).
5. C. K. Chui, An Introduction to Wavelets. Academic Press, San Diego (1992).
6. S. G. Mallat, A theory for multiresolution signal decomposition: the wavelet representation. IEEE Trans. Pattern Anal. Mach. Intell. 11(7), 674-693 (1989).
7. A. N. Tikhonov and V. Y. Arsenin, Solutions of III Posed Problems. W. H. Winston, Washington, D C (1977).
8. C. A. Micchelli, Interpolation of scattered data: distance matrices and conditionally positive definite functions. Construct. Approx. 2, 11-22 (1986).
9. N. R. Lomb, Least-Squares frequency analysis of unequally spaced data, Astrophys. Space Sci. 39, 447-462 (1976).
10. M. D. Buhmann and C. A. Micchelli, Spline prewavelets for non-uniform knots, Numerische Mathematik 61, 455-474 (1992).
11. M. D. Buhmann, Multiquadratic prewavelets on non-equally spaced centres, Technical Report 94-06, Seminar für Angewandte Mathematik Eidgenössische Technische Hochshule (July 1994).
12. W. Sweldens, Lifting scheme: a construction of second-generation wavelets, SPIE Proc. Wavelet Appl. Sign. Image Process. III, to be published (1995).
13. H. Murase and S. K. Nayar, Learning and recognition of 3D objects from appearance, Int. J. Comput. Vis. 1-24 (January 1995).
14. E. Horowitz and S. Sahni, Fundamentals of Data Structures. Computer Science Press Int. Inc., Rockville, MD (1993).
15. R. A. Devore, B. Jawerth and V. A. Popov, Compression of wavelet decompositions, Am. J. Math. 123-129 (1992).
16. R. A. Devore, B. Jawerth and B. J. Lucier, Image compression through wavelet transform coding, IEEE Trans. Inf. Theory 38(2), 719-746 (1992).
17. M. Unser, A. Aldroubi and M. Eden, On the asymptotic convergence of β-spline wavelets to Gabor functions, IEEE Trans. Inf. Theory 38, 864-872 (March 1992).
18. M. Unser, A. Aldroubi and M. Eden, A family of polynomial spline wavelet transforms, Sign. Process. 30, 141-162 (1993).
19. 2 polynomial spline pyramid, IEEE Trans. Pattern Anal. Mach. Intell. 15(4), 364-378 (April 1993).