Titlebook: Mathematical Approaches to Biomolecular Structure and Dynamics; Jill P. Mesirov,Klaus Schulten,De Witt Sumners Book 1996 Springer-Verlag N

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John E. Hearst,Yaoming Shiindependent context, whereas the experiments were conducted for a uniform distribution, and (3) the previous lower bound was valid for nets with one hidden layer only. These experiments also seem to indicate that networks with two hidden layers have Vapnik-Chervonenkis dimension roughly equal to the

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Donald J. Dichmann,Yiwei Li,John H. Maddocksgative signals arrive to each neuron, are non-linear, so that their existence and uniqueness is not easily established except for the case of feedforward (or backpropagation) networks [1]. We examine two sub-classes of networks: balanced, and damped networks and obtain stability conditions in each c

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John F. Marko,Eric D. Siggialutions to real engineering problems may not ameliorate the difficulties of classification problems, but rather obscure and postpone them. In particular, we doubt that the design of neural networks for solving interesting nontrivial engineering problems will be any easier than other large scale engi

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Benedict J. Leimkuhler,Sebastian Reich,Robert D. Skeelks composed of binary-valued information- processing units, highly abstracted versions of biological neurons, either by mathematical analysis or by computer simulation, have emerged as a third route towards a better understanding of the brain, and possibly of the human mind. Long remaining - with the exceptio978-3-642-97239-3Series ISSN 0939-3145

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Jill P. Mesirov,Pablo Tamayo,Robert J. Nagled of binary-valued information- processing units, highly abstracted versions of biological neurons, either by mathematical analysis or by computer simulation, have emerged as a third route towards a better understanding of the brain, and possibly of the human mind. Long remaining - with the exceptio