Neural Networks and Learning Machines
Neural Networks and Learning Machines
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作者：
S. Haykin
用于计算机工程、电气工程和计算机科学系提供的研究生水平神经网络课程。《神经网络和学习机器》第三版以其透彻性和可读性而闻名。这本组织良好且完全更新的文本仍然是从工程角度对神经网络最全面的处理。这是专业工程师和研究科学家的理想选择。本文中用于计算机实验的Matlab代码可在以下网站下载：http://www.pearsonhighered.com/haykin/重新聚焦，修订和重命名以反映神经网络和学习机器的二元性，这一版本认识到，当这些主题一起研究时，主题更加丰富。从神经网络和机器学习中提取的想法被混合起来，以执行超出任何一方独立能力的改进学习任务。
For graduate-level neural network courses offered in the departments of Computer Engineering, Electrical Engineering, and Computer Science. Neural Networks and Learning Machines, Third Edition is renowned for its thoroughness and readability. This well-organized and completely upto-date text remains the most comprehensive treatment of neural networks from an engineering perspective. This is ideal for professional engineers and research scientists. Matlab codes used for the computer experiments in the text are available for download at: http://www.pearsonhighered.com/haykin/ 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.