Neural Network Models

[1]  Hong Chen,et al.  Universal approximation to nonlinear operators by neural networks with arbitrary activation functions and its application to dynamical systems , 1995, IEEE Trans. Neural Networks.

[2]  Shun-ichi Amari,et al.  Network information criterion-determining the number of hidden units for an artificial neural network model , 1994, IEEE Trans. Neural Networks.

[3]  D. M. Titterington,et al.  Neural Networks: A Review from a Statistical Perspective , 1994 .

[4]  Hong Chen,et al.  Approximations of continuous functionals by neural networks with application to dynamic systems , 1993, IEEE Trans. Neural Networks.

[5]  Hava T. Siegelmann,et al.  Analog computation via neural networks , 1993, [1993] The 2nd Israel Symposium on Theory and Computing Systems.

[6]  Brian D. Ripley,et al.  Statistical aspects of neural networks , 1993 .

[7]  Kurt Hornik,et al.  Some new results on neural network approximation , 1993, Neural Networks.

[8]  Michael I. Jordan Constrained supervised learning , 1992 .

[9]  Hava T. Siegelmann,et al.  On the computational power of neural nets , 1992, COLT '92.

[10]  James C. Bezdek,et al.  On the relationship between neural networks, pattern recognition and intelligence , 1992, Int. J. Approx. Reason..

[11]  Jeffrey L. Elman,et al.  Finding Structure in Time , 1990, Cogn. Sci..

[12]  Pineda,et al.  Generalization of back-propagation to recurrent neural networks. , 1987, Physical review letters.

[13]  James L. McClelland,et al.  Parallel distributed processing: explorations in the microstructure of cognition, vol. 1: foundations , 1986 .

[14]  P. Werbos,et al.  Beyond Regression : "New Tools for Prediction and Analysis in the Behavioral Sciences , 1974 .

[15]  F ROSENBLATT,et al.  The perceptron: a probabilistic model for information storage and organization in the brain. , 1958, Psychological review.