Using either the dot product or cosine similarity for SPA

[ChielWijs]

@xchoo

Hi @ChielWijs, and welcome back to the Nengo forums!

Thanks , I have just started work on my master’s thesis, so i’ll expect that this wont be the last you see of me.

@xchoo

1. The dot product is easier to compute (just a matrix multiplication vs needing a division). Because of this, implementing it in a neural network is fairly simple since you can embed the dot product in the connection weights (if you are comparing to a static vector), or use the Product network to build a dot-product network (if you are comparing two variable vectors).

For my use, I only need the spa.similarity() function to compare my model output to a vocabulary, so no need to implement it in the network itself, as I will just be using a probe to collect the signal, and analyse it after simulation.

Thank you for the insights.