This documentation is for a development version. Click here for the latest stable release (v1.1.0).


Functions to evaluate analytically derived equations related to the SPA.


prob_cleanup(similarity, dimensions, vocab_size)

Estimate the chance of successful cleanup.

nengo_spa.math.prob_cleanup(similarity, dimensions, vocab_size)[source]

Estimate the chance of successful cleanup.

This returns the chance that, out of vocab_size randomly chosen vectors, none of them will be closer to a particular vector than the value given by similarity. To use this, compare your noisy vector with the ideal vector, pass that value in as the similarity parameter, and set vocab_size to be the number of competing vectors.

Requires SciPy.