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IJCNN
2000
IEEE
14 years 2 months ago
Analog Hardware Implementation of the Random Neural Network Model
This paper presents a simple continuous analog hardware realization of the Random Neural Network (RNN) model. The proposed circuit uses the general principles resulting from the u...
Hossam Abdelbaki, Erol Gelenbe, Said E. El-Khamy
ISCAS
2003
IEEE
117views Hardware» more  ISCAS 2003»
14 years 3 months ago
Learning temporal correlations in biologically-inspired aVLSI
Temporally-asymmetric Hebbian learning is a class of algorithms motivated by data from recent neurophysiology experiments. While traditional Hebbian learning rules use mean firin...
Adria Bofill-i-Petit, Alan F. Murray
IJCNN
2008
IEEE
14 years 4 months ago
Wafer-scale integration of analog neural networks
Abstract— This paper introduces a novel design of an artificial neural network tailored for wafer-scale integration. The presented VLSI implementation includes continuous-time a...
Johannes Schemmel, Johannes Fieres, Karlheinz Meie...
ISCAS
2006
IEEE
144views Hardware» more  ISCAS 2006»
14 years 3 months ago
A VLSI spike-driven dynamic synapse which learns only when necessary
— We describe an analog VLSI circuit implementing spike-driven synaptic plasticity, embedded in a network of integrate-and-fire neurons. This biologically inspired synapse is hi...
S. Mitra, Stefano Fusi, Giacomo Indiveri
ICANN
2005
Springer
14 years 3 months ago
A Hardware/Software Framework for Real-Time Spiking Systems
Abstract. One focus of recent research in the field of biologically plausible neural networks is the investigation of higher-level functions such as learning, development and modu...
Matthias Oster, Adrian M. Whatley, Shih-Chii Liu, ...