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Publication
Artificial neural networks, electronic circuits, and gene networks are some examples of systems that can be modeled as networks, that is, as collections of interconnected nodes. I...
NN
1998
Springer
13 years 7 months ago
1998
Springer
A recurrent neural network can possess multiple stable states, a property that many brain theories have implicated in learning and memory. There is good evidence for such multista...
NN
2011
Springer
12 years 10 months ago
2011
Springer
Neurodynamical models of working memory (WM) should provide mechanisms for storing, maintaining, retrieving, and deleting information. Many models address only a subset of these a...
AI
2002
Springer
13 years 7 months ago
2002
Springer
Neural network ensemble is a learning paradigm where many neural networks are jointly used to solve a problem. In this paper, the relationship between the ensemble and its compone...
IJCNN
2006
IEEE
14 years 1 months ago
2006
IEEE
— This paper shows the advantage of using neural network modularity over conventional learning schemes to approximate complex functions. Indeed, it is difficult for artificial ...