Pattern classification of non-sparse data using optimal interpolative nets

Neurocomputing

Volumn 10, Issue 4, 1996, Pages 385-403

  Eltoft, Torbjørn ^a   DeFigueiredo, Rui J P ^b  

^a UNIVERSITY OF TROMSØ   (Norway)

^b UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Classification; Neural network; Pattern recognition; Statistical classification

Indexed keywords

INTERPOLATION; LEARNING ALGORITHMS; LEAST SQUARES APPROXIMATIONS; OPTIMAL SYSTEMS; PATTERN RECOGNITION; PATTERN RECOGNITION SYSTEMS; RECURSIVE FUNCTIONS; STATISTICAL METHODS;

GENERALIZED FOCK SPACE FORMULATION; NONSPARSE DATA; STATISTICAL PATTERN CLASSIFICATION;

NEURAL NETWORKS;

ALGORITHM; ARTICLE; ARTIFICIAL NEURAL NETWORK; PATTERN RECOGNITION; PRIORITY JOURNAL;

EID: 0342468016     PISSN: 09252312     EISSN: None     Source Type: Journal    
DOI: 10.1016/0925-2312(95)00045-3     Document Type: Article

References (17)

1. M.R. Azimi-Sadjadi, S. Sheedvash and F.O. Trujillo, Recursive dynamic node creation in multilayer neural networks, IEEE Trans. Neural Networks 5 (2) (1993) 242-256.
2. R.J.P. deFigueiredo, A generalized fock space framework for nonlinear system and signal analysis, IEEE Trans. Circuits Syst. 30 (9) (1983) 637-647.
3. R.J.P. deFigueiredo, A new nonlinear functional analytic framework for modeling artificial neural networks, Proc. 1990 IEEE Int. Symp. on Circuits and Systems (ISCAS) (New Orleans, 1990) 723-726.
4. R.J.P. deFigueiredo, An optimal matching-score net for pattern classification, Proc. 1990 Int. Joint Conf. on Neural Networks (IJCNN) 3 (San Diego, 1990) 909-916.
5. R.J.P. deFigueiredo and G. Chen, Optimal interpolation on a generalized fock space of analytic functions, in C.K. Chui et al., eds, Approximation Theory (Academic Press, New York, 1989) 247-250.
6. P.A. Devijver and J. Kittler, On the nearest neighbor rule, Proc. 5th Int. Conf. on Pattern Recognition (1980) 72-80.
7. P.A. Devijver and J. Kittler, On the edited nearest neighbor rule with the resolution of a controversy, Report R410, Philips Res. Lab., 1979.
8. R.O. Duda and P.E. Hart, Pattern Classification and Scene Analysis (John Wiley & Sons, New York, 1973).
9. K. Fukunaga, Introduction to Statistical Pattern Recognition (Academic Press, Boston, 1990).
10. R. Hecht-Nielsen, Theory of the back-propagation network, Proc. 1989 Int. Joint Conf. on Neural Networks (IJCNN) 1 (New York, 1989) 593-611.
11. T. Kohonen, An introduction to neural computing, Neural Networks 1 (1988) 3-16.
12. T. Kohonen, The 'neural' phonetic typewriter, IEEE Comput. 21 (3) (1988) 11-12.
13. S.K. Sin and R.J.P. deFigueiredo, An incremental fine adjustment algorithm for the design of optimal interpolating neural networks, Int. J. Pattern Recognition and Artificial Intelligence 5 (4) (1991) 563-579.
14. S.K. Sin and R.J.P. deFigueiredo, Efficient learning procedures for optimal interpolative nets, Neural Networks 6 (1993) 99-113.
15. I. Tomek, An experiment with the edited nearest-neighbor rule, IEEE Trans. Systems Man Cybernet. 6 (1976) 448-452.
16. D.L. Wilson, Asymptotic properties of nearest neighbor rules using edited data, IEEE Trans. Systems, Man Cybernet. 2 (1972) 408-421.
17. J.M. Zurada, Introduction to Artificial Neural Systems (West, St. Paul, 1992).