The brain-like architecture of artificial neural networks makes them ideal for tackling problems that are too difficult for conventional architectures, specifically problems that involve pattern recognition or other perceptual tasks.
Neuro-Computers: Optimization Based Learning provides an intermediate-level exposition of the exciting world of neuro-computers. It presents the importance of neuro-computing to artificial intelligence, giving historical background and present-day implementation options. The book demonstrates the superiority of the adaptive search strategy over conventional fixed parameter searches performed by backpropagation algorithms. It then explores global optimization strategy and presents genetic algorithms as viable methods to train neuro computers on non-trivial problems.
This self-contained volume is delivered in a format that is suitable for graduate students, as well as researchers who want to begin work in neuro-computing or related artificial intelligence applications.
具體描述
讀後感
評分
評分
評分
評分
用戶評價
相關圖書
本站所有內容均為互聯網搜索引擎提供的公開搜索信息，本站不存儲任何數據與內容，任何內容與數據均與本站無關，如有需要請聯繫相關搜索引擎包括但不限於百度，google,bing,sogou 等
© 2025 qciss.net All Rights Reserved. 小哈圖書下載中心 版权所有