GENERALIZATION CAPABILITY OF FEEDFORWARD NEURAL NETWORKS FOR PATTERN RECOGNITION TASKS

vi LIST OF ABBREVIATIONS xi

[1]  Martin Anthony,et al.  Quantifying Generalization in Linearly Weighted Neural Networks , 1994, Complex Syst..

[2]  R. Lippmann,et al.  An introduction to computing with neural nets , 1987, IEEE ASSP Magazine.

[3]  Yong Liu,et al.  Unbiased estimate of generalization error and model selection in neural network , 1995, Neural Networks.

[4]  Julius T. Tou,et al.  Pattern Recognition Principles , 1974 .

[5]  Sompolinsky,et al.  Statistical mechanics of learning from examples. , 1992, Physical review. A, Atomic, molecular, and optical physics.

[6]  Lawrence R. Rabiner,et al.  A tutorial on hidden Markov models and selected applications in speech recognition , 1989, Proc. IEEE.

[7]  R. Palmer,et al.  Introduction to the theory of neural computation , 1994, The advanced book program.

[8]  B. Yegnanarayana,et al.  Artificial neural networks for pattern recognition , 1994 .

[9]  David Haussler,et al.  What Size Net Gives Valid Generalization? , 1989, Neural Computation.

[10]  Hermann Ney,et al.  On the Probabilistic Interpretation of Neural Network Classifiers and Discriminative Training Criteria , 1995, IEEE Trans. Pattern Anal. Mach. Intell..

[11]  D.R. Hush,et al.  Progress in supervised neural networks , 1993, IEEE Signal Processing Magazine.

[12]  David Haussler,et al.  Learnability and the Vapnik-Chervonenkis dimension , 1989, JACM.

[13]  Leslie G. Valiant,et al.  A theory of the learnable , 1984, CACM.

[14]  Mohamad T. Musavi,et al.  On the Generalization Ability of Neural Network Classifiers , 1994, IEEE Trans. Pattern Anal. Mach. Intell..

[15]  Peter J. W. Rayner,et al.  Generalization and PAC learning: some new results for the class of generalized single-layer networks , 1995, IEEE Trans. Neural Networks.

[16]  Bayya Yegnanarayana,et al.  Studies on object recognition from degraded images using neural networks , 1995, Neural Networks.

[17]  J. Makhoul,et al.  Linear prediction: A tutorial review , 1975, Proceedings of the IEEE.

[18]  Simon Haykin,et al.  Neural Networks: A Comprehensive Foundation , 1998 .

[19]  Geoffrey E. Hinton,et al.  Learning internal representations by error propagation , 1986 .

[20]  J. Dombi Membership function as an evaluation , 1990 .

[21]  Eduardo D. Sontag,et al.  Feedforward Nets for Interpolation and Classification , 1992, J. Comput. Syst. Sci..

[22]  David Lowe,et al.  Radial basis function networks , 1998 .

[23]  Richard P. Lippmann,et al.  An introduction to computing with neural nets , 1987 .