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A temporally and spatially local spike-based backpropagation algorithm to enable training in hardware
Although signed gradient values are a challenge for spike-based representation, we tackle this by splitting the gradient signal into positive and negative streams.
A simple and efficient SNN and its performance & robustness evaluation method to enable hardware implementation
Second, we develop a computationally efficient (15000 x) and accurate (correlation of 0. 98) method to evaluate the performance of the network without standard recognition tests.
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