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» VLSI Implementation of Neural Networks
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FPL
2008
Springer
125views Hardware» more  FPL 2008»
13 years 9 months ago
Reconfigurable platforms and the challenges for large-scale implementations of spiking neural networks
FPGA devices have witnessed popularity in their use for the rapid prototyping of biological Spiking Neural Network (SNNs) applications, as they offer the key requirement of reconf...
Jim Harkin, Fearghal Morgan, Steve Hall, Piotr Dud...
DATE
2008
IEEE
134views Hardware» more  DATE 2008»
14 years 2 months ago
Scalable Architecture for on-Chip Neural Network Training using Swarm Intelligence
This paper presents a novel architecture for on-chip neural network training using particle swarm optimization (PSO). PSO is an evolutionary optimization algorithm with a growing ...
Amin Farmahini Farahani, Seid Mehdi Fakhraie, Saee...
TVLSI
1998
88views more  TVLSI 1998»
13 years 7 months ago
Time multiplexed color image processing based on a CNN with cell-state outputs
—A practical system approach for time-multiplexing cellular neural network (CNN) implementations suitable for processing large and complex images using small CNN arrays is presen...
Lei Wang, José Pineda de Gyvez, Edgar S&aac...
APIN
2002
121views more  APIN 2002»
13 years 7 months ago
Applying Learning by Examples for Digital Design Automation
This paper describes a new learning by example mechanism and its application for digital circuit design automation. This mechanism uses finite state machines to represent the infer...
Ben Choi
FCCM
2009
IEEE
147views VLSI» more  FCCM 2009»
13 years 11 months ago
FPGA Accelerated Simulation of Biologically Plausible Spiking Neural Networks
Artificial neural networks are a key tool for researchers attempting to understand and replicate the behaviour and intelligence found in biological neural networks. Software simul...
David Thomas, Wayne Luk