| 书目名称 | Neural Networks and Statistical Learning | | 编辑 | Ke-Lin Du,M. N. S. Swamy | | 视频video | | | 概述 | Extensively updated second edition with new chapters on spar coding, deep learning, big data and cloud computing.A comprehensive introduction to neural networks and statistical learning from a practic | | 图书封面 |  | | 描述 | .This book provides a broad yet detailed introduction to neural networks and machine learning in a statistical framework. A single, comprehensive resource for study and further research, it explores the major popular neural network models and statistical learning approaches with examples and exercises and allows readers to gain a practical working understanding of the content. This updated new edition presents recently published results and includes six new chapters that correspond to the recent advances in computational learning theory, sparse coding, deep learning, big data and cloud computing..Each chapter features state-of-the-art descriptions and significant research findings. The topics covered include:.• multilayer perceptron;.• the Hopfield network;.• associative memory models;• clustering models and algorithms;.• t he radial basis function network;.• recurrent neural networks;.• nonnegative matrix factorization;.• independent component analysis;.•probabilistic and Bayesian networks; and.• fuzzy sets and logic..Focusing on the prominent accomplishments and their practical aspects, this book provides academic and technical staff, as well as graduate students and researchers | | 出版日期 | Textbook 2019Latest edition | | 关键词 | Data Mining, Data Fusion and Ensemble Learning; Multilayer Perceptrons; Neural Networks; Pattern Recogn | | 版次 | 2 | | doi | https://doi.org/10.1007/978-1-4471-7452-3 | | isbn_softcover | 978-1-4471-7454-7 | | isbn_ebook | 978-1-4471-7452-3 | | copyright | Springer-Verlag London Ltd., part of Springer Nature 2019 |
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发表于 2025-3-21 17:43:41
