Like other methods, the important step of normalization of the probability density functions that are represented in our neural implementation is left to other mechanisms. Recently we have been working on methods to include normalization in the inference transformation (which takes place in the connection weights). We have recently submitted this work for publication. The supporting Nengo and Matlab code can be downloaded below.
Open the Normalization.3k.good.nef, and run it to regenerate the data in the paper. To put an input into the model, run the normalization_input_reader.py script, which takes the input_matrix.txt and generates a node that will give the correct input.
To generate the plots, run nengo_plotgen (read instructions in that file).
Just to get the 'ideal' solution (no neurons), run the normalization_noneurons_paper.m, which is the easiest.