Recurrent Neural Networks
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. T...
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| Formato: | Online |
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| Idioma: | inglês |
| Publicado em: |
IntechOpen
2021
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| Acesso em linha: | ONIX_20210420_9789537619084_34 |
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| _version_ | 1869521944110432256 |
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| collection | Directory of Open Access Books |
| description | 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. |
| format | Online |
| id | doab-20.500.12854ir-64678 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2021 |
| publishDateRange | 2021 |
| publishDateSort | 2021 |
| publisher | IntechOpen |
| publisherStr | IntechOpen |
| record_format | ojs |
| spelling | doab-20.500.12854ir-646782024-04-14T10:28:19Z Recurrent Neural Networks Hu, Xiaolin Balasubramaniam, P. Neural networks & fuzzy systems thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence 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. 2021-04-20T14:53:12Z 2021-04-20T14:53:12Z 2008 book ONIX_20210420_9789537619084_34 9789537619084 9789535157953 https://directory.doabooks.org/handle/20.500.12854/64678 eng image/jpeg n/a https://www.intechopen.com/books https://mts.intechopen.com/storage/books/6118/authors_book/authors_book.pdf IntechOpen IntechOpen 10.5772/68 10.5772/68 78a36484-2c0c-47cb-ad67-2b9f5cd4a8f6 9789537619084 9789535157953 IntechOpen 402 open access |
| spellingShingle | Neural networks & fuzzy systems thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence Recurrent Neural Networks |
| title | Recurrent Neural Networks |
| title_full | Recurrent Neural Networks |
| title_fullStr | Recurrent Neural Networks |
| title_full_unstemmed | Recurrent Neural Networks |
| title_short | Recurrent Neural Networks |
| title_sort | recurrent neural networks |
| topic | Neural networks & fuzzy systems thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence |
| topic_facet | Neural networks & fuzzy systems thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence |
| url | ONIX_20210420_9789537619084_34 |