Titlebook: An Introduction to Neural Network Methods for Differential Equations; Neha Yadav,Anupam Yadav,Manoj Kumar Book 2015 The Author(s) 2015 Cel

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Abgangwasser aus Stärkefabrikenon to artificial neural systems, 2001) [8], Nielsen (Neurocomputing, 1990 [9] in terms of the development of architectures and algorithms that are widely used today. The history of neural networks has been divided in four stages: Beginning of neural networks, First golden age, Quiet Years and Renewe

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Abgangwasser aus Papier-Fabrikenetwork in terms of activation functions. Different architectures of neural network like feed forward, feed backward, radial basis function network, multilayer perceptron neural network and cellular network etc., is described. Backpropagation and other training algorithms have been also discussed in this chapter.

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2191-530X h to the renewed interest of the 1980s. A general introduction to neural networks and learning technologies is presented in Section III. This section also includes the description of the multil978-94-017-9815-0978-94-017-9816-7Series ISSN 2191-530X Series E-ISSN 2191-5318

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2191-530X ence and engineering. The emphasis is placed on a deep understanding of the neural network techniques, which has been presented in a mostly heuristic and intuitive manner. This approach will enable the reader to understand the working, efficiency and shortcomings of each neural network technique for