Hierarchical Temporal Memory Based System Including Nodes with Input or Output Variables of Disparate Properties

• US 20070192262A1
• Filed: 02/28/2007
• Published: 08/16/2007
• Est. Priority Date: 02/10/2006
• Status: Active Grant

• Current Assignee: Numenta, Inc.
• Original Assignee: Numenta, Inc.
• Inventors: Astier, Frank, Marianetti, Ronald
• Granted Patent: US 7,941,389 B2
• Time in Patent Office: Days
• US Class Current: 706/12
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: G06N 3/045 Combinations of networks
• CPC Class Codes: G06N 3/047 Probabilistic or stochastic networks
• CPC Class Codes: G06N 3/049 Temporal neural networks, e.g. delay elements, oscillating neurons or pulsed inputs
• CPC Class Codes: G06N 3/08 Learning methods

Abstract

An hierarchical temporal memory network having at least one node configured to receive at least two variables of different properties. The at least two variables have different data types, different data sizes, or represent different physical or logical properties in the hierarchical temporal memory network. By using the node receiving variables of different properties, the hierarchical temporal memory network can be configured more flexibly and efficiently because a separate node is not needed to receive, process, and output variables of different properties.

Claims

1. An HTM network comprising:

a first link coupled to carry a first variable;

a second link coupled to carry a second variable, the first variable and the second variable having a different property; and

a node coupled to the first link and second link to receive the first and second variables.

2. The HTM network of claim 1 wherein a data type of the first variable is different from a data type of the second variable.

3. The HTM network of claim 1 wherein a size of the first variable is different from a size of the second variable.

4. An HTM network comprising:

a sending node generating an output, the output comprising at least a first portion and a second portion;

a first receiving node receiving a first portion of the output of the sending node; and

a second receiving node receiving a second portion of the output of the sending node.

5. The HTM network of claim 4, wherein the first portion of the output and the second portion of the output partially overlap.