Neural Networks and Statistical Learning
暫譯: 神經網絡與統計學習
Du, Ke-Lin, Swamy, M. N. S.
- 出版商: Springer
- 出版日期: 2016-09-27
- 售價: $5,390
- 貴賓價: 9.5 折 $5,121
- 語言: 英文
- 頁數: 824
- 裝訂: Quality Paper - also called trade paper
- ISBN: 1447170474
- ISBN-13: 9781447170471
海外代購書籍(需單獨結帳)
商品描述
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 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.商品描述(中文翻譯)
提供一個廣泛但深入的神經網絡和機器學習的統計框架介紹，本書為學習和進一步研究提供了一個全面的資源。所有主要的流行神經網絡模型和統計學習方法都涵蓋在內，每一章都有範例和練習，以發展對內容的實際工作理解。
二十五章中的每一章都包括了各自主題的最先進描述和重要研究結果。廣泛的內容涵蓋了多層感知器（multilayer perceptron）、霍普菲爾德網絡（Hopfield network）、聯想記憶模型、聚類模型和算法、徑向基函數網絡（radial basis function network）、遞迴神經網絡（recurrent neural networks）、主成分分析（principal component analysis）、非負矩陣分解（nonnegative matrix factorization）、獨立成分分析（independent component analysis）、判別分析（discriminant analysis）、支持向量機（support vector machines）、核方法（kernel methods）、強化學習（reinforcement learning）、概率和貝葉斯網絡（probabilistic and Bayesian networks）、數據融合和集成學習（ensemble learning）、模糊集和邏輯（fuzzy sets and logic）、神經模糊模型（neurofuzzy models）、硬體實現，以及一些機器學習主題。還包括生物識別/生物信息學和數據挖掘的應用。
專注於顯著的成就及其實際方面，學術和技術人員、研究生及研究者將會發現這本書為神經網絡、模式識別、信號處理、機器學習、計算智能和數據挖掘領域提供了堅實的基礎和全面的參考。
作者簡介
Ke-Lin Du is currently the Chief Scientist at Enjoyor Inc., China. He is also an Affiliate Associate Professor in Department of Electrical and Computer Engineering at Concordia University, Canada. Prior to joining Enjoyor Inc. in 2012, he held positions with Huawei Technologies, the China Academy of Telecommunication Technology, the Chinese University of Hong Kong, the Hong Kong University of Science and Technology, and Concordia University. He has published two books and over 50 papers, and filed over 15 patents. His current research interests include signal processing, neural networks, intelligent systems, and wireless communications. He is a Senior Member of the IEEE.M.N.S. Swamy is currently a Research Professor and holder of the Concordia Tier I Research Chair Signal Processing in the Department of Electrical and Computer Engineering, Concordia University, where he was Dean of the Faculty of Engineering and Computer Science from 1977 to 1993 and the founding Chair of the EE department. He has published extensively in the areas of circuits, systems and signal processing, and co-authored five books. Professor Swamy is a Fellow of the IEEE, IET (UK) and EIC (Canada), and has received many IEEE-CAS awards, including the Guillemin-Cauer award in 1986, as well as the Education Award and the Golden Jubilee Medal, both in 2000.
作者簡介(中文翻譯)
Ke-Lin Du 目前是中國 Enjoyor Inc. 的首席科學家。他同時也是加拿大康考迪亞大學電機與計算機工程系的兼任副教授。在2012年加入 Enjoyor Inc. 之前，他曾在華為技術有限公司、中國通信科技學院、香港中文大學、香港科技大學及康考迪亞大學擔任職位。他已出版兩本書籍和超過50篇論文，並申請了超過15項專利。他目前的研究興趣包括信號處理、神經網絡、智能系統和無線通信。他是 IEEE 的資深會員。M.N.S. Swamy 目前是康考迪亞大學電機與計算機工程系的研究教授及信號處理 Tier I 研究主席，曾於1977年至1993年擔任工程與計算機科學學院院長，並且是電機工程系的創始主席。他在電路、系統和信號處理領域發表了大量的研究成果，並共同撰寫了五本書籍。Swamy 教授是 IEEE、IET（英國）和 EIC（加拿大）的會士，並獲得多項 IEEE-CAS 獎項，包括1986年的 Guillemin-Cauer 獎，以及2000年的教育獎和金禧獎。
