Comparisons of Single- and Multiple-Hidden-Layer Neural Networks
暂无分享,去创建一个
[1] Tom Heskes,et al. A theoretical comparison of batch-mode, on-line, cyclic, and almost-cyclic learning , 1996, IEEE Trans. Neural Networks.
[2] Laurene V. Fausett,et al. Fundamentals Of Neural Networks , 1993 .
[3] M.H. Hassoun,et al. Fundamentals of Artificial Neural Networks , 1996, Proceedings of the IEEE.
[4] Ken-ichi Funahashi,et al. On the approximate realization of continuous mappings by neural networks , 1989, Neural Networks.
[5] Laurene V. Fausett,et al. Fundamentals Of Neural Networks , 1994 .
[6] Tony R. Martinez,et al. The general inefficiency of batch training for gradient descent learning , 2003, Neural Networks.
[7] J. Nazuno. Haykin, Simon. Neural networks: A comprehensive foundation, Prentice Hall, Inc. Segunda Edición, 1999 , 2000 .
[8] Eduardo D. Sontag,et al. Feedback Stabilization Using Two-Hidden-Layer Nets , 1991, 1991 American Control Conference.
[9] A. Barron. Approximation and Estimation Bounds for Artificial Neural Networks , 1991, COLT '91.
[10] Simon Haykin,et al. Neural Networks: A Comprehensive Foundation , 1998 .
[11] Geoffrey E. Hinton,et al. Learning internal representations by error propagation , 1986 .
[12] Kurt Hornik,et al. Multilayer feedforward networks are universal approximators , 1989, Neural Networks.
[13] Takéhiko Nakama,et al. Theoretical analysis of batch and on-line training for gradient descent learning in neural networks , 2009, Neurocomputing.
[14] Philipp Slusallek,et al. Introduction to real-time ray tracing , 2005, SIGGRAPH Courses.
[15] Kurt Hornik,et al. Some new results on neural network approximation , 1993, Neural Networks.