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» VLSI Implementation of Neural Networks
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GLVLSI
1998
IEEE
124views VLSI» more  GLVLSI 1998»
13 years 12 months ago
Non-Refreshing Analog Neural Storage Tailored for On-Chip Learning
In this research, we devised a new simple technique for statically holding analog weights, which does not require periodic refreshing. It further contains a mechanism to locally u...
Bassem A. Alhalabi, Qutaibah M. Malluhi, Rafic A. ...
ICANN
2007
Springer
13 years 9 months ago
Solving Selected Classification Problems in Bioinformatics Using Multilayer Neural Network Based on Multi-Valued Neurons (MLMVN)
A multilayer neural network based on multi-valued neurons (MLMVN) is a new powerful tool for solving classification, recognition and prediction problems. This network has a number ...
Igor N. Aizenberg, Jacek M. Zurada
FPGA
2009
ACM
201views FPGA» more  FPGA 2009»
14 years 2 months ago
A high-performance FPGA architecture for restricted boltzmann machines
Despite the popularity and success of neural networks in research, the number of resulting commercial or industrial applications have been limited. A primary cause of this lack of...
Daniel L. Ly, Paul Chow
IWANN
1999
Springer
13 years 12 months ago
A Modular Attractor Model of Semantic Access
This paper presents results from lesion experiments on a modular attractor neural network model of semantic access. Real picture data forms the basis of perceptual input to the mod...
William Power, Ray J. Frank, D. John Done, Neil Da...
ESANN
2006
13 years 9 months ago
Extended model of conditioned learning within latent inhibition
Due to the various and dynamic nature of stimuli, decisions of intelligent agents must rely on the coordination of complex cognitive systems. This paper precisely focusses on a gen...
Nicolas Gomond, Jean Marc Salotti