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» VLSI Implementation of Neural Networks
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NIPS
2000
13 years 9 months ago
A Silicon Primitive for Competitive Learning
Competitive learning is a technique for training classification and clustering networks. We have designed and fabricated an 11transistor primitive, that we term an automaximizing ...
David Hsu, Miguel Figueroa, Chris Diorio
TNN
1998
96views more  TNN 1998»
13 years 7 months ago
Noise suppressing sensor encoding and neural signal orthonormalization
In this paper we regard first the situation where parallel channels are disturbed by noise. With the goal of maximal information conservation we deduce the conditions for a transf...
Rüdiger W. Brause, M. Rippl
RECONFIG
2008
IEEE
225views VLSI» more  RECONFIG 2008»
14 years 2 months ago
A Hardware Filesystem Implementation for High-Speed Secondary Storage
Platform FPGAs are capable of hosting entire Linuxbased systems including standard peripherals, integrated network interface cards and even disk controllers on a single chip. File...
Ashwin A. Mendon, Ron Sass
ISVLSI
2003
IEEE
118views VLSI» more  ISVLSI 2003»
14 years 1 months ago
Networks-On-Chip: The Quest for On-Chip Fault-Tolerant Communication
In this paper, we discuss the possibility of achieving onchip fault-tolerant communication based on a new communication paradigm called stochastic communication. Specifically, for...
Radu Marculescu
ESANN
2008
13 years 9 months ago
Visual focus with spiking neurons
Attentional focusing can be implemented with a neural field [1], which uses a discharge rate code. As an alternative, we propose in the present work an implementation based on spik...
Sylvain Chevallier, Philippe Tarroux