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An FPGA-based model suitable for evolution and development of spiking neural networks

AbstractWe propose a digital neuron model suitable for evolving and growing heterogeneous spiking neural networks on FPGAs using a piecewise linear approximation of the Quadratic Integrate and Fire (QIF) model. A network of 161 neurons and 1610 synapses with 4210 times realtime neuron simulation speed was simulated and synthesized for a Virtex-5 chip.

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Associated Researchers

Hooman Shayani

Senior Manager, Senior Principal AI Research Scientist
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