A note on error bounds for approximation in inner product spaces

Circuits, Systems, and Signal Processing

Volumn 15, Issue 4, 1996, Pages 515-518

  Dingankar, Ajit ^a   Sandberg, Irwin W ^b  

^a IBM   (United States)

^b The University of Texas at Austin   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; APPROXIMATION THEORY; COMPUTATIONAL METHODS; ERRORS;

INNER PRODUCT SPACE; SIGMOIDAL NONLINEARITIES;

NEURAL NETWORKS;

EID: 0029717957     PISSN: 0278081X     EISSN: None     Source Type: Journal    
DOI: 10.1007/BF01183158     Document Type: Article

References (7)

1. A. R. Barron, Universal approximation bounds for superpositions of a sigmoidal function, IEEE Transactions on Information Theory, vol. 39, no. 3, pp. 930-945, May 1993.
2. E. W. Cheney, Topics in approximation theory, Course Notes for Mathematics 393D, Department of Mathematics, The University of Texas at Austin, Spring 1993.
3. G. Cybenko, Approximation by superposition of a single function, Mathematics of Control, Signals and Systems, vol. 2, pp. 303-314, 1989.
4. F. Girosi and G. Anzellotti, Rates of convergence for radial basis functions and neural networks, in Artificial Neural Networks with Applications in Speech and Vision, Chapman & Hall, 1993.
5. L. K. Jones, A simple lemma on greedy approximation in Hubert space and convergence rates for projection pursuit regression and neural network training, The Annals of Statistics, vol. 20, pp. 608-613, March 1992.
6. G. Pisier, Remarques sur un resultat non publie de B. Maurey, Seminaire d'Analyse Fonctionelle, vol. 1, no. 12, Ecole Polytechnique, Centre de Mathematiques, Palaiseau, 1980-81.
7. I. W. Sandberg, General structures for classification, IEEE Transactions on Circuits and Systems-I: Fundamental Theory and Applications, vol. 41, no. 5, pp. 372-376, May 1994.