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Sách: Principles of Artificial Neural Networks: 3rd Edition (Advanced Series in Circuits & Systems) (Advanced Series in Circuits and Systems) 3rd edition Edition Tác giả: Daniel Graupe Artificial neural networks are most suitable for solving problems that are complex, ill-defined, highly nonlinear, of many and different variables, and/or



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A neural circuit, is a population of neurons interconnected by synapses to carry out a specific function when activated. Neural circuits interconnect to one another to form large scale brain networks. Biological neural networks have inspired the design of artificial neural networks.



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This book is the first published textbook of AI in chemical engineering, and provides broad and in-depth coverage of AI programming, AI principles, expert systems, and neural networks in chemical engineering. This book introduces the computational means and methodologies that are used to enable computers to perform intelligent engineering tasks. A key goal is to move beyond the principles of

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3rd Edition. — World Scientific, 2013. — 363 p. — ISBN: 978-9814522731. Artificial neural networks are most suitable for solving problems that are complex, ill-defined, highly nonlinear, of many and different variables, and/or stochastic. Such problems are abundant in medicine, in finance, in security and beyond. This volume covers the basic theory and architecture of the...

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Sách: Principles of Artificial Neural Networks: 3rd Edition (Advanced Series in Circuits & Systems) (Advanced Series in Circuits and Systems) 3rd edition Edition Tác giả: Daniel Graupe Artificial neural networks are most suitable for solving problems that are complex, ill-defined, highly nonlinear, of many and different variables, and/or

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Basic Principles of ANN Design The basic principles of the artificial neural networks (ANNs) were first formulated by McCulloch and Pitts in 1943, in terms of five assumptions, as follows: (1) The activity of a neuron (ANN) is all-or-nothing. (2) A certain fixed number of synapses larger than 1 must be excited within a given interval of neural addition for a neuron to be excited. (3) The only

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