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Biologically compatible neural networks with reconfigurable hardware
2015
Microprocessors and microsystems
This paper presents a reconfigurable hardware neuro-simulator specifically designed to emulate biophysically accurate and biologically compatible neural networks. The platform is based on FPGA technology which is used to create real-time custom neuroprocessors with floating point accuracy and a novel hybrid time-event driven architecture for synaptic integration. Through a series of experiments the dynamics of the neuroprocessors are evaluated and compared with real neuron responses. The
doi:10.1016/j.micpro.2015.09.003
fatcat:nhjuuqwcmncavg7pwxquef7b34