GENERALIZATION CAPABILITY OF FEEDFORWARD NEURAL NETWORKS FOR PATTERN RECOGNITION TASKS
暂无分享,去创建一个
[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 .