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ENGL
2008
142views more  ENGL 2008»
13 years 7 months ago
A Solid-State Neuron for Spiking Neural Network Implementation
This paper presents a compact analog neuron cell incorporating an array of charge-coupled synapses connected via a common output terminal. The novel silicon synapse is based on a t...
Yajie Chen, Steve Hall, Liam McDaid, Octavian Buiu...
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...
EH
1999
IEEE
351views Hardware» more  EH 1999»
13 years 12 months ago
Evolvable Hardware or Learning Hardware? Induction of State Machines from Temporal Logic Constraints
Here we advocate an approach to learning hardware based on induction of finite state machines from temporal logic constraints. The method involves training on examples, constraint...
Marek A. Perkowski, Alan Mishchenko, Anatoli N. Ch...
ISCAS
2011
IEEE
278views Hardware» more  ISCAS 2011»
12 years 11 months ago
A programmable axonal propagation delay circuit for time-delay spiking neural networks
— we present an implementation of a programmable axonal propagation delay circuit which uses one first-order logdomain low-pass filter. Delays may be programmed in the 550ms rang...
Runchun Wang, Craig T. Jin, Alistair McEwan, Andr&...
EUROCAST
2003
Springer
130views Hardware» more  EUROCAST 2003»
14 years 25 days ago
A Model of Neural Inspiration for Local Accumulative Computation
This paper explores the computational capacity of a novel local computational model that expands the conventional analogical and logical dynamic neural models, based on the charge ...
José Mira, Miguel Angel Fernández, M...