Spatio-temporal learning algorithms in hierarchical temporal networks
First Claim
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1. A processing node in a computing device, comprising:
- a processor; and
a spatial pooler configured to;
detect spatial patterns in an input signal, the spatial patterns in the input signal changing over time; and
generate a series of spatial pooler outputs in sparse distributed code, each spatial pooler output indicating the detected spatial patterns at a time; and
a temporal pooler configured to;
associate temporal sequences of the detected spatial patterns by storing temporal relationships between the series of spatial pooler outputs; and
generate a temporal pooler output based on the stored temporal relationships between the series of spatial pooler outputs.
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Abstract
A spatio-temporal learning node is a type of HTM node which learns both spatial and temporal groups of sensed input patterns over time. Spatio-temporal learning nodes comprise spatial poolers which are used to determine spatial groups in a set of sensed input patterns. The spatio-temporal learning nodes further comprise temporal poolers which are used to determine groups of sensed input patterns that temporally co-occur. A spatio-temporal learning network is a hierarchical network including a plurality of spatio-temporal learning nodes.
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Citations
20 Claims
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1. A processing node in a computing device, comprising:
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a processor; and a spatial pooler configured to; detect spatial patterns in an input signal, the spatial patterns in the input signal changing over time; and generate a series of spatial pooler outputs in sparse distributed code, each spatial pooler output indicating the detected spatial patterns at a time; and a temporal pooler configured to; associate temporal sequences of the detected spatial patterns by storing temporal relationships between the series of spatial pooler outputs; and generate a temporal pooler output based on the stored temporal relationships between the series of spatial pooler outputs. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
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10. A method of detecting and processing sequences of spatial patterns in an input, comprising:
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at a spatial pooler of a processing node, detecting spatial patterns in an input signal, the spatial patterns in the input signal changing over time; at the spatial pooler, generating a series of spatial pooler outputs in sparse distributed code, each spatial pooler output indicating the detected spatial patterns at a time; at a temporal pooler of the processing node, associating temporal sequences of the detected spatial patterns by storing temporal relationships between the series of spatial pooler outputs; and at the temporal pooler, generating a sequence processor output based on the stored temporal relationships between the series of spatial pooler outputs. - View Dependent Claims (11, 12, 13, 14, 15, 16, 17, 18)
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19. A non-transitory computer readable storage medium structured to store instructions executable by a processor in a computing device, the instructions, when executed cause the processor to:
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detect spatial patterns in an input signal, the spatial patterns in the input signal changing over time; generate a series of spatial pooler outputs in sparse distributed code, each spatial pooler output indicating the detected spatial patterns at a time; associate temporal sequences of the detected spatial patterns by storing temporal relationships between the series of spatial pooler outputs; and generate a sequence processor output based on the stored temporal relationships between the series of spatial pooler outputs. - View Dependent Claims (20)
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Specification