Hardware implementation of a bio-plausible neuron model for evolution and growth of spiking neural networks on FPGA

TY - GEN

T1 - Hardware implementation of a bio-plausible neuron model for evolution and growth of spiking neural networks on FPGA

AU - Shayani, Hooman

AU - Bentley, Peter J.

AU - Tyrrell, Andrew M.

PY - 2008

Y1 - 2008

N2 - We propose a digital neuron model suitable for evolving and growing heterogeneous spiking neural networks on FPGAs by introducing a novel flexible dendrite architecture and the new PLAQIF (Piecewise-Linear Approximation of Quadratic Integrate and Fire) soma model. A network of 161 neurons and 1610 synapses was simulated, implemented, and verified on a Virtex-5 chip with 4210 times real-time speed with 1 ms resolution. The parametric flexibility of the soma model was shown through a set of experiments.

AB - We propose a digital neuron model suitable for evolving and growing heterogeneous spiking neural networks on FPGAs by introducing a novel flexible dendrite architecture and the new PLAQIF (Piecewise-Linear Approximation of Quadratic Integrate and Fire) soma model. A network of 161 neurons and 1610 synapses was simulated, implemented, and verified on a Virtex-5 chip with 4210 times real-time speed with 1 ms resolution. The parametric flexibility of the soma model was shown through a set of experiments.

KW - SYSTEMS

UR - http://www.scopus.com/inward/record.url?scp=51949097982&partnerID=8YFLogxK

M3 - Conference contribution

SN - 978-0-7695-3166-3

SP - 236

EP - 243

BT - PROCEEDINGS OF THE 2008 NASA/ESA CONFERENCE ON ADAPTIVE HARDWARE AND SYSTEMS

PB - IEEE Computer Society

CY - LOS ALAMITOS

ER -