Title :
A Hybrid Bio-inspired System: Hardware Spiking Neural Network Incorporating Hebbian Learning with Microprocessor Based Evolutionary Control Algorithm
Author :
Allen, David ; Halliday, David M. ; Tyrrell, Andy M.
Author_Institution :
Southampton Univ., Southampton
Abstract :
The objective of the work reported in this paper was the development of an application that combined evolution and learning on a hardware platform. This was achieved on two different platforms: a COTS FPGA and a new device specifically designed for bio-inspired implementations, termed the POEtic chip. The learning process is based around a spiking neural network with Hebbian learning.
Keywords :
Hebbian learning; evolutionary computation; field programmable gate arrays; neural nets; Hebbian learning; POEtic chip; evolutionary control algorithm; hardware spiking neural network; hybrid bio-inspired system; Artificial neural networks; Control systems; Evolution (biology); Field programmable gate arrays; Fires; Hebbian theory; Microprocessors; Neural network hardware; Neural networks; Neurons;
Conference_Titel :
Evolutionary Computation, 2006. CEC 2006. IEEE Congress on
Conference_Location :
Vancouver, BC
Print_ISBN :
0-7803-9487-9
DOI :
10.1109/CEC.2006.1688681
