Recurrent Neural Networks for Temporal Data Processing
The RNNs (Recurrent Neural Networks) are a general case of artificial neural networks where the connections are not feed-forward ones only. In RNNs, connections between units form directed cycles, providing an implicit internal memory. Those RNNs are adapted to problems dealing with signals evolving...
Saved in:
| Other Authors: | |
|---|---|
| Format: | Electronic Book Chapter |
| Language: | English |
| Published: |
IntechOpen
2011
|
| Subjects: | |
| Online Access: | DOAB: download the publication DOAB: description of the publication |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
MARC
| LEADER | 00000naaaa2200000uu 4500 | ||
|---|---|---|---|
| 001 | doab_20_500_12854_64931 | ||
| 005 | 20210420 | ||
| 003 | oapen | ||
| 006 | m o d | ||
| 007 | cr|mn|---annan | ||
| 008 | 20210420s2011 xx |||||o ||| 0|eng d | ||
| 020 | |a 631 | ||
| 020 | |a 9789533076850 | ||
| 020 | |a 9789535155218 | ||
| 040 | |a oapen |c oapen | ||
| 024 | 7 | |a 10.5772/631 |c doi | |
| 041 | 0 | |a eng | |
| 042 | |a dc | ||
| 072 | 7 | |a UYQ |2 bicssc | |
| 100 | 1 | |a Cardot, Hubert |4 edt | |
| 700 | 1 | |a Cardot, Hubert |4 oth | |
| 245 | 1 | 0 | |a Recurrent Neural Networks for Temporal Data Processing |
| 260 | |b IntechOpen |c 2011 | ||
| 300 | |a 1 electronic resource (114 p.) | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 506 | 0 | |a Open Access |2 star |f Unrestricted online access | |
| 520 | |a The RNNs (Recurrent Neural Networks) are a general case of artificial neural networks where the connections are not feed-forward ones only. In RNNs, connections between units form directed cycles, providing an implicit internal memory. Those RNNs are adapted to problems dealing with signals evolving through time. Their internal memory gives them the ability to naturally take time into account. Valuable approximation results have been obtained for dynamical systems. | ||
| 540 | |a Creative Commons |f https://creativecommons.org/licenses/by-nc-sa/3.0/ |2 cc |4 https://creativecommons.org/licenses/by-nc-sa/3.0/ | ||
| 546 | |a English | ||
| 650 | 7 | |a Artificial intelligence |2 bicssc | |
| 653 | |a Neural networks & fuzzy systems | ||
| 856 | 4 | 0 | |a www.oapen.org |u https://mts.intechopen.com/storage/books/102/authors_book/authors_book.pdf |7 0 |z DOAB: download the publication |
| 856 | 4 | 0 | |a www.oapen.org |u https://directory.doabooks.org/handle/20.500.12854/64931 |7 0 |z DOAB: description of the publication |