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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Xiaolin Hu and P. Balasubramaniam | |
dc.date.accessioned | 2017-04-30T13:31:39Z | - |
dc.date.available | 2017-04-30T13:31:39Z | - |
dc.date.issued | 2008 | |
dc.identifier.isbn | 978-953-7619-08-4 | |
dc.identifier.uri | http://hdl.handle.net/123456789/131122 | - |
dc.description.abstract | The concept of neural network originated from neuroscience, and one of its primitive aims is to help us understand the principle of the central nerve system and related behaviors through mathematical modeling. The first part of the book is a collection of three contributions dedicated to this aim. The second part of the book consists of seven chapters, all of which are about system identification and control. The third part of the book is composed of Chapter 11 and Chapter 12, where two interesting RNNs are discussed, respectively.The fourth part of the book comprises four chapters focusing on optimization problems. Doing optimization in a way like the central nerve systems of advanced animals including humans is promising from some viewpoints. | |
dc.language.iso | eng | |
dc.publisher | InTech | |
dc.relation.isbasedon | 10.5772/68 | |
dc.relation.uri | http://www.intechopen.com/books/recurrent_neural_networks | |
dc.rights.uri | CC BY-NC-SA (姓名標示-非商業性-相同方式分享) | |
dc.source | InTech | |
dc.subject.classification | Computer and Information Science | |
dc.subject.classification | Numerical Analysis and Scientific Computing | |
dc.title | Recurrent Neural Networks | |
dc.type | 電子教課書 | |
dc.classification | 自然科學類 | |
Theme: | 教科書-自然科學類 |
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