Hippocampus-Inspired Spiking Neural Network on FPGA

TY - CONF

T1 - Hippocampus-Inspired Spiking Neural Network on FPGA

AU - Mokhtar, Maizura

AU - Halliday, David M.

AU - Tyrrell, Andy M.

PY - 2008

Y1 - 2008

N2 - 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 ail 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 oil all FPGA, in order to take advantage of these two characteristics as well as to achieve autonomy for a neuro-controller device.

AB - 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 ail 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 oil all FPGA, in order to take advantage of these two characteristics as well as to achieve autonomy for a neuro-controller device.

KW - Bio-inspired Hardware

KW - Spiking Neural Network

KW - FPGA

KW - ROBOTS

UR - http://www.scopus.com/inward/record.url?scp=70349881931&partnerID=8YFLogxK

M3 - Paper

SP - 362

EP - 371

T2 - 8th International Conference on Evolvable Systems

Y2 - 1 September 2008

ER -