Yes, that's right. Yuwei
On Mon, Apr 4, 2016 at 1:33 PM, Sebastián Narváez <[email protected]> wrote: > Hi Yuwei, Thanks for your response, things are much clearer now. I was > refering to this "if": > > if permanence > 0 and self.predictedSegmentDecrement > 0: > > Now, if I understand what you said, the connected synapses must be taken > into account as much as the non connected, but active ones, for the > formation of the matchingSegments and matchingCells variables. Their > decrement will only be made when the next element of the sequence arrives > and the matchingCells~Segments do not match with the current active cells. > Is that right? > > On Mon, Apr 4, 2016 at 12:50 PM, Yuwei Cui <[email protected]> wrote: > >> Hello Sebastián, >> >> Please see my answers below: >> >>> >>> 1) What do the matchingSegments and matchingCells represent? >>> >> >> I think we recently include the logic here to model "long-term >> depression". That is if the segment has sufficient activity at time t, but >> does not become active at time t+1, it represents a potential false >> prediction and should be punished. "sufficient activity" here means number >> of active inputs is above minThreshold. matchingSegments and matchingCells >> are used to determine predicted but inactive cells at the next time step >> (see line 376 of learnOnSegments). >> >> This logic speeds up the forgetting of false predictions, but it should >> be used with caution. If your problems has multiple correct predictions, >> then it is OK to have some false predictions. Generally speaking, the ratio >> between permanenceIncrement and predictedSegmentDecrement determines how >> many multiple predictions can the model make at any time. >> >> >>> 2) minThreshold is supposed to be the minimum number of synapses a >>> segment must have in order to be considered for bursting, what does it do >>> here? >>> >> >> activationThreshold is the threshold for activation of a segment: if a >> segment has more than activationThreshold number of active synapses, it >> will fire a dendritic spike and depolarize the cell body. >> >> minThreshold is typically lower than activationThreshold and is only used >> in learning phase (not in inference phase). It are used in two places as >> far as I know. >> >> 1. If the number of synapses active on a segment is at least this >> threshold, it is selected as the best matching cell in a bursting column. >> (see function bestMatchingSegment) >> >> 2. It is used to determine predicted but inactive cells and segments as >> described above. >> >> >>> 3) As I see it, the if also grabs the permanneces above the connected >>> threshold, why is that? >>> >> >> I am not sure which "if" you are referring to here. Could you clarify >> your question? >> >> Yuwei >> >> >
