A Hardware Implementation of a Network of Functional Spiking Neurons with Hebbian Learning

Abstract. In this paper we present a functional model of a spiking neuron intended for hardware implementation. Some features of biological spiking neuabstracted, while preserving the functionality of the network, in order to define an architecture with low implementation cost in field programmable gate arrays (FPGAs). Adaptation of synaptic weights is implemented with hebbian learning. As an example application we present a frequency discriminator to verify the computing capabilities of a generic network of our neuron model.

• Type: Conference
• Year: 2004
• Where: BIOADIT
• Authors: Andres Upegui, Carlos Andrés Peña-Reyes, Eduardo Sanchez
• Keywords: BIOADIT 2004, Information Technology, Low Implementation Cost, Programmable Gate Arrays, Spiking Neuron