Neural Networks and Statistical Learning PDF
By:Ke-Lin Du,M. N. S. Swamy
Published on 2013-12-09 by Springer Science & Business Media
Providing a broad but in-depth introduction to neural network and machine learning in a statistical framework, this book provides a single, comprehensive resource for study and further research. All the major popular neural network models and statistical learning approaches are covered with examples and exercises in every chapter to develop a practical working understanding of the content. Each of the twenty-five chapters includes state-of-the-art descriptions and important research results on the respective topics. The broad coverage includes the multilayer perceptron, the Hopfield network, associative memory models, clustering models and algorithms, the radial basis function network, recurrent neural networks, principal component analysis, nonnegative matrix factorization, independent component analysis, discriminant analysis, support vector machines, kernel methods, reinforcement learning, probabilistic and Bayesian networks, data fusion and ensemble learning, fuzzy sets and logic, neurofuzzy models, hardware implementations, and some machine learning topics. Applications to biometric/bioinformatics and data mining are also included. Focusing on the prominent accomplishments and their practical aspects, academic and technical staff, graduate students and researchers will find that this provides a solid foundation and encompassing reference for the fields of neural networks, pattern recognition, signal processing, machine learning, computational intelligence, and data mining.
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Book ID of Neural Networks and Statistical Learning's Books is wzK8BAAAQBAJ, Book which was written byKe-Lin Du,M. N. S. Swamyhave ETAG "/xT7y0mXqhQ"
Book which was published by Springer Science & Business Media since 2013-12-09 have ISBNs, ISBN 13 Code is 9781447155713 and ISBN 10 Code is 1447155718
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Book which have "824 Pages" is Printed at BOOK under CategoryComputers
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