SWITCHED CAPACITOR{BASED IMPLEMENTATION OF INTEGRATE{AND{FIRE NEURAL NETWORKS
Daniel Hajt · 2003
This paper is dealing with an analogue implementation of an Integrate and Fire neural network consisting of the learning synapse, which is a vital part of a self-organising neural network and the neurone designed according its biological counterpart. The proposed synapse includes a post-synaptic potential forming block, which makes it possible to uniquely characterise each synapse output in a complete neural network. This approach is conceptually closer to its biological counterpart. The design uses switched capacitor technique in order to be able to make the above described modications realisable. K e y w o r d s: integrate and re neurones, learning synapses, neural networks implementation, built-in learning, hebbian learning rule