A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf
.
Homogeneous Spiking Neuromorphic System for Real-World Pattern Recognition
2015
IEEE Journal on Emerging and Selected Topics in Circuits and Systems
A neuromorphic chip that combines CMOS analog spiking neurons and memristive synapses offers a promising solution to brain-inspired computing, as it can provide massive neural network parallelism and density. Previous hybrid analog CMOS-memristor approaches required extensive CMOS circuitry for training, and thus eliminated most of the density advantages gained by the adoption of memristor synapses. Further, they used different waveforms for pre and post-synaptic spikes that added undesirable
doi:10.1109/jetcas.2015.2433552
fatcat:jd6l2uhpmjhindanx7boqkdkgq