A Fast Spatial Pool Learning Algorithm of Hierarchical Temporal Memory Based on Minicolumn’s Self-Nomination

<div>HTM workflow. It describes that, after the input is encoded, trained in the space pool, and trained in the time pool, the subsequent prediction can be made according to the memory.</div>

Computational Intelligence and Neuroscience

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Figure 1

Figure 1: A Fast Spatial Pool Learning Algorithm of Hierarchical Temporal Memory Based on Minicolumn’s Self-Nomination 