I have a few questions on a particular topic, corresponding to the HTM algorithm:
When there is no predictive cell that is active, then all the cells of the column burst. How to choose the winner cell? The paper and video give some clarity, but I still have some doubts, so I would like to clarify.
Let us suppose (only for the sake of example and discussion of current topic) there are 10 columns with 10 cells each, so 90 total cells in the system.
- Each cell contains several segments. So each segment would be a binary vector of 100 dimensions, 1 denoting an active synapse, and 0 denoting an inactive one, correct?
- If no segment is active, I pick the segment with the highest number of active synapses, and the cell corresponding to that segment as the winner cell - is that correct? So suppose column 2 burst, in absence of any predictive neuron. Suppose, col.2 cell 5 contains 6 segments, and segment 1 has 13 active synapses, which is the highest, across all cells in col. 2. Then I pick segment 1, and the corresponding cell 5 in column 2 as the winner cell.
- Do I increase the permanence of cell 5 (the winner cell) or should I increase the permanence of all the bursting cells?