{"product_id":"9780971732117","title":"Neural Network Design (2nd Edition)","description":"This book, by the authors of the Neural Network Toolbox for MATLAB, provides a clear and detailed coverage of fundamental neural network architectures and learning rules. In it, the authors emphasize a coherent presentation of the principal neural networks, methods for training them and their applications to practical problems.\u003cp\u003eFeatures\u003c\/p\u003e\u003cp\u003eExtensive coverage of training methods for both feedforward networks (including multilayer and radial basis networks) and recurrent networks. In addition to conjugate gradient and Levenberg-Marquardt variations of the backpropagation algorithm, the text also covers Bayesian regularization and early stopping, which ensure the generalization ability of trained networks.\u003c\/p\u003e\u003cp\u003eAssociative and competitive networks, including feature maps and learning vector quantization, are explained with simple building blocks.\u003c\/p\u003e\u003cp\u003eA chapter of practical training tips for function approximation, pattern recognition, clustering and prediction, along with five chapters presenting detailed real-world case studies.\u003c\/p\u003e\u003cp\u003eDetailed examples and numerous solved problems. Slides and comprehensive demonstration software can be downloaded from hagan.okstate.edu\/nnd.html.\u003c\/p\u003e","brand":"Martin Hagan","offers":[{"title":"Default Title","offer_id":47013426757872,"sku":"9780971732117","price":30.0,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0737\/7593\/9824\/files\/9780971732117_p0.jpg?v=1763880432","url":"https:\/\/shop-qa.barnesandnoble.com\/products\/9780971732117","provider":"Barnes \u0026 Noble (DEV)","version":"1.0","type":"link"}