Fixed-weight on-line learning
暂无分享,去创建一个
A. Steven Younger | Peter R. Conwell | Neil E. Cotter | A. S. Younger | N. E. Cotter | P. R. Conwell | N. Cotter
[1] Alan S. Lapedes,et al. A self-optimizing, nonsymmetrical neural net for content addressable memory and pattern recognition , 1986 .
[2] I. Gould,et al. Return electron transfer within geminate radical ion pairs. Observation of the marcus inverted region , 1987 .
[3] J. L. Gould,et al. Learning by Instinct , 1987 .
[4] Robert M. Farber,et al. Programming a massively parallel, computation universal system: Static behavior , 1987 .
[5] Pineda,et al. Generalization of back-propagation to recurrent neural networks. , 1987, Physical review letters.
[6] D. O. Hebb,et al. The organization of behavior , 1988 .
[7] Ronald J. Williams,et al. A Learning Algorithm for Continually Running Fully Recurrent Neural Networks , 1989, Neural Computation.
[8] W. Pitts,et al. A Logical Calculus of the Ideas Immanent in Nervous Activity (1943) , 2021, Ideas That Created the Future.
[9] Mark A. Holler,et al. VLSI Implementations of Learning and Memory Systems: A Review , 1990, NIPS 1990.
[10] Peter R. Conwell,et al. Fixed-weight networks can learn , 1990, 1990 IJCNN International Joint Conference on Neural Networks.
[11] L. B. Almeida. A learning rule for asynchronous perceptrons with feedback in a combinatorial environment , 1990 .
[12] Peter R. Conwell,et al. Methuselah networks and optimal control , 1990, 1990 IJCNN International Joint Conference on Neural Networks.
[13] Barak A. Pearlmutter. Dynamic recurrent neural networks , 1990 .
[14] Anders Krogh,et al. Introduction to the theory of neural computation , 1994, The advanced book program.
[15] N. E. Cotter,et al. Learning algorithms and fixed dynamics , 1991, IJCNN-91-Seattle International Joint Conference on Neural Networks.
[16] Peter R. Conwell,et al. Universal Approximation by Phase Series and Fixed-Weight Networks , 1993, Neural Computation.
[17] K M Johnson,et al. Optoelectronic array that computes error and weight modification for a bipolar optical neural network. , 1993, Applied optics.
[18] R. Palmer,et al. Introduction to the theory of neural computation , 1994, The advanced book program.
[19] Emile Fiesler,et al. Neural network classification and formalization , 1994 .
[20] Tom Heskes,et al. How Dependencies between Successive Examples Affect On-Line Learning , 1996, Neural Computation.