Hippocampus-inspired spiking neural network on FPGA

Abstract

There is now a great interest in exploiting the capabilities of hardware devices; especially the reconfigurable properties of FPGA to implement and study the dynamics of neural networks, specifically a biological inspired neural network. FPGA has a much greater appeal than other modes of implementation because an FPGA implementation offers the flexibility of simple software (re-)configuration in comparison to other digital ASICs. In this paper a hippocampus-inspired spiking neural network is implemented on an FPGA, in order to take advantage of these two characteristics as well as to achieve autonomy for a neuro-controller device. © 2008 Springer-Verlag Berlin Heidelberg.