| 書目名稱 | Neural Networks and Statistical Learning | | 編輯 | Ke-Lin Du,M. N. S. Swamy | | 視頻video | http://file.papertrans.cn/664/663712/663712.mp4 | | 概述 | Provides a comprehensive introduction to neural networks and statistical learning ensuring a broad yet in-depth coverage of the techniques focusing on the prominent accomplishments in practical aspect | | 圖書封面 |  | | 描述 | .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 an | | 出版日期 | Textbook 20141st edition | | 關(guān)鍵詞 | Data Mining, Data Fusion and Ensemble Learning; Multilayer Perceptrons; Neural Networks; Pattern Recogn | | 版次 | 1 | | doi | https://doi.org/10.1007/978-1-4471-5571-3 | | isbn_softcover | 978-1-4471-7047-1 | | isbn_ebook | 978-1-4471-5571-3 | | copyright | Springer-Verlag London 2014 |
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