[nengo-user] About the model "RBM Deep Belief Network for Visual Digit Recognition"

[Zonghua Gu]

We built a FPGA for simulation of Spiking NN, and are looking for
models as test applications. We hope to use the digit recognition
example here http://models.nengo.ca/node/28. But from reading the
paper, and the provided digit.py file:

Tang Y, Eliasmith C. Deep networks for robust visual
recognition[C]//Proceedings of the 27th International Conference on
Machine Learning (ICML-10). 2010: 1055-1062.

It seems it is not a spiking neural network. But the documentation
says "A spiking neuron model for digit recognition, created by
training an RBM Deep Belief Network on the MNIST database, then
converting the resulting model to spiking neurons via Nengo." Could
you please explain how the conversion is done?


-- 
Zonghua Gu
Zhejiang University