Poisson Rate Encoding about snn_toolbox HOT 4 CLOSED

Hi @abdul-muneeb7 , sorry for the delayed response.

The poisson encoding happens here. The line that probably causes the non-binary spikes you observed is here. This step assumes that the input samples contained in x_b_l are normalized, such that max(x_b_l) == 1, in which case this line does not modify the spikes. It is possible however that even after normalizing the dataset globally (which you did), an individual batch x_b_l may not have a maximum of 1. Another possibility is that you did not use max norm but some percentile norm so that the global maximum is different from 1. I'd recommend removing line 302 as it was only intended for the special case of networks with binary weights.

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Sure, Thanks for getting back to me @rbodo. I have seen this poisson encoding code part, here but just wanted to learn more from the explanation in any of your papers.

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The basic idea is that at each time step you draw a random number and if it is below the poisson rate parameter, you get a spike. The higher the rate parameter, the higher the probability of generating a spike.

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Got it. Thanks, Prof. @rbodo.

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