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Neural Networks and Learning Machines读书介绍

类别 页数 译者 网友评分 年代 出版社
书籍 936页 8.7 2020 Pearson
定价 出版日期 最近访问 访问指数
USD 252.40 2020-02-20 … 2020-03-06 … 95
主题/类型/题材/标签
神经网络,机器学习,MachineLearning,人工智能,NeuralNetworks,计算机,AI,计算机科学,
作者
Simon O. Haykin      ISBN:9780131471399    原作名/别名:《Neural Networks: A Comprehensive Foundation》
内容和作者简介
Neural Networks and Learning Machines摘要

For graduate-level neural network courses offered in the departments of Computer Engineering, Electrical Engineering, and Computer Science. Renowned for its thoroughness and readability, this well-organized and completely up-to-date text remains the most comprehensive treatment of neural networks from an engineering perspective. Refocused, revised and renamed to reflect the duality of neural networks and learning machines, this edition recognizes that the subject matter is richer when these topics are studied together. Ideas drawn from neural networks and machine learning are hybridized to perform improved learning tasks beyond the capability of either independently.

作者简介

Simon Haykin,于1953年获得英国伯明翰大学博士学位,目前为加拿大McMaster大学电子与计算机工程系教授、通信研究实验室主任。他是国际电子电气工程界的*名学者,曾获得IEEE McNaughton金奖。他是加拿大皇家学会院士、IEEE会士,在神经网络、通信、自适应滤波器等领域成果颇丰,*有多部标准教材。

本书后续版本
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