Recurrent neural networks have been used to solve various problems such as combinatorial optimization [1], encoding information in a network with the help of a master network [2], etc. The approach is to cast the problem in terms of an energy function that is then minimized by the corresponding netw
โฆ LIBER โฆ
The analysis of the faulty behavior of synchronous neural networks
โ Scribed by Belfore, L.A., II; Johnson, B.W.
- Book ID
- 119771775
- Publisher
- IEEE
- Year
- 1991
- Tongue
- English
- Weight
- 662 KB
- Volume
- 40
- Category
- Article
- ISSN
- 0018-9340
No coin nor oath required. For personal study only.
๐ SIMILAR VOLUMES
The importance of being synchronous in n
โ
Behzad Kamgar-Parsi; Behrooz Kamgar-Parsi
๐
Article
๐
1988
๐
Elsevier Science
๐
English
โ 72 KB
Artificial neural networks in the analys
โ
V. Korz, U. Schade, U. Laubenstein, H. Hendrichs
๐
Article
๐
1995
๐
Springer
๐
English
โ 372 KB
State space analysis of synchronous spik
โ
Markus Diesmann; Marc-Oliver Gewaltig; Stefan Rotter; Ad Aertsen
๐
Article
๐
2001
๐
Elsevier Science
๐
English
โ 225 KB
An optimally evolved connective ratio of
โ
Chao-Yi Dong, Kwang-Hyun Cho
๐
Article
๐
2012
๐
BioMed Central
๐
English
โ 465 KB
Synchronization analysis of coupled conn
โ
Qiankun Song
๐
Article
๐
2009
๐
Elsevier Science
๐
English
โ 438 KB
On the behavior of some associative neur
โ
R. Braham; J. O. Hamblen
๐
Article
๐
1988
๐
Springer-Verlag
๐
English
โ 666 KB
Since Hopfield published his work on an associative memory model, a large number of works have studied the model from several angles and showed in particular its weaknesses, and presented ways to overcome them. Most of the proposed solutions seem to us however not biologically plausible. In this pap