Data processing: artificial intelligence – Neural network – Learning task
Reexamination Certificate
2011-05-03
2011-05-03
Vincent, David R (Department: 2129)
Data processing: artificial intelligence
Neural network
Learning task
Reexamination Certificate
active
07937342
ABSTRACT:
An HTM node learns a plurality of groups of sensed input patterns over time based on the frequency of temporal adjacency of the input patterns. An HTM node receives a new sensed input, the HTM node assigns probabilities as to the likelihood that the new sensed input matches each of the plurality of learned groups. The HTM node then combines this probability distribution (may be normalized) with previous state information to assign probabilities as to the likelihood that the new sensed input is part of each of the learned groups of the HTM node. Then, as described above, the distribution over the set of groups learned by the HTM node is passed to a higher level node. This process is repeated at higher level nodes to infer a cause of the newly sensed input.
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Hoey, J., “Hie
George Dileep
Hawkins Jeffrey C
Jaros Robert Gilchrist
Fenwick & West LLP
Numenta, Inc.
Vincent David R
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