資料來源: Google Book
Limitations and future trends in neural computation
- 其他作者: Ablameyko, Sergey,
- 出版: Amsterdam ;Burke, VA :Tokyo : IOS Press ;Ohmsha ©2003.
- 稽核項: 1 online resource (ix, 245 pages) :illustrations.
- 叢書名: NATO science series. Series III, Computer and systems sciences,v. 186
- 標題: Neural Networks. , COMPUTERS Neural Networks. , Electronic books. , Neural computers Congresses. , Réseaux neuronaux (Informatique) Congrès. , Neural computers. , COMPUTERS , Electronic books Conference proceedings. , Ordinateurs neuronaux Congrès. , Neural networks (Computer science) , Réseaux neuronaux (Informatique) , Neural computers , Conference papers and proceedings. , Ordinateurs neuronaux , Neural networks (Computer science) Congresses.
- ISBN: 4274905810 , 9784274905810
- ISBN: 1586033247 , 4274905810 , 1387-6694 ;
- 試查全文@TNUA:
- 附註: "Published in cooperation with NATO Scientific Affairs Division." Includes bibliographical references and index. Cover; Title page; Preface; Contents; Chapter 1. Continuous Problem Solving and Computational Suspiciousness; Chapter 2. The Complexity of Computing with Continuous Time Devices; Chapter 3. Energy-Based Computation with Symmetric Hopfield Nets; Chapter 4. Computational Complexity and the Elusiveness of Global Optima; Chapter 5. Impact of Neural Networks on Signal Processing and Communications; Chapter 6. From Clustering Data to Traveling as a Salesman: Empirical Risk Approximation as a Learning Theory; Chapter 7. Learning High-dimensional Data.
- 摘要: This work reports critical analyses on complexity issues in the continuum setting and on generalization to new examples, which are two basic milestones in learning from examples in connectionist models. It also covers up-to-date developments in computational mathematics.
- 電子資源: https://dbs.tnua.edu.tw/login?url=https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=110141
- 系統號: 005321702
- 資料類型: 電子書
- 讀者標籤: 需登入
- 引用網址: 複製連結
This work reports critical analyses on complexity issues in the continuum setting and on generalization to new examples, which are two basic milestones in learning from examples in connectionist models. It also covers up-to-date developments in computational mathematics.
來源: Google Book
來源: Google Book
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