Formal analysis of HTM Spatial Pooler performance under predefined
  operation conditions
  This paper introduces mathematical formalism for Spatial (SP) of Hierarchical
Temporal Memory (HTM) with a spacial consideration for its hardware
implementation. Performance of HTM network and its ability to learn and adjust
to a problem at hand is governed by a large set of parameters. Most of
parameters are codependent which makes creating efficient HTM-based solutions
challenging. It requires profound knowledge of the settings and their impact on
the performance of system. Consequently, this paper introduced a set of
formulas which are to facilitate the design process by enhancing tedious
trial-and-error method with a tool for choosing initial parameters which enable
quick learning convergence. This is especially important in hardware
implementations which are constrained by the limited resources of a platform.
The authors focused especially on a formalism of Spatial Pooler and derive at
the formulas for quality and convergence of the model. This may be considered
as recipes for designing efficient HTM models for given input patterns.
