System and method for automatic topology determination in a hierarchical-temporal network

• US 20090116413A1
• Filed: 10/17/2008
• Published: 05/07/2009
• Est. Priority Date: 10/18/2007
• Status: Abandoned Application

• Current Assignee: Numenta, Inc.
• Original Assignee: Numenta, Inc.
• Inventors: George, Dileep
• Application Number:
  US12/288,185
• Publication Number:
  US 20090116413A1
• Time in Patent Office: Days
• US Class Current: 370/256
• CPC Class Codes: G06N 3/045 Combinations of networks
• CPC Class Codes: G06N 3/049 Temporal neural networks, e.g. delay elements, oscillating neurons or pulsed inputs

Abstract

A system and method for automatically analyzing data streams in a hierarchical and temporal network to identify node positions and the network topology in order to generate a hierarchical model of the temporal or spatial data. The system and method receives data streams, identifies a correlation between the data streams, partitions/clusters the data streams based upon the identified correlation and forms a current level of a hierarchical temporal network by having each cluster of data streams be an input to a hierarchical temporal network node. After training the nodes, each of the nodes creates a new data stream and these data streams are correlated and partitioned/clustered and are input into a node at a next level. The process can repeat until a desired portion of the network topology is determined.

Claims

1. A method for creating a hierarchical model for temporal data, comprising the steps of:

(a) receiving a plurality of data streams comprising the temporal data;

(b) identifying a mutual information value between pairs of said data streams, said mutual information value representing the mutual information between said pair of data streams;

(c) clustering said data streams into at least two clusters based upon said mutual information;

(d) creating a current level of the hierarchical model based upon said clusters, wherein said current level generates additional data streams; and

(e) repeating steps (b)-(d) for said additional data streams to create different levels of the hierarchical model.

2. The method of claim 1, wherein the hierarchical model represents a hierarchical temporal memory network.

3. The method of claim 1, wherein the step of creating a current level includes the step of creating a node for each cluster.

4. The method of claim 1, wherein said mutual information represents a correlation between pairs of said data streams.

5. The method of claim 1, wherein the data streams can be received from different levels of the hierarchical model.

6. The method of claim 1, wherein said mutual information is based upon at least one of spatial correspondence or temporal correspondence.

13. A computer program product embodied on a computer readable medium which when executed performs the method steps of claim 1.

7. A system for creating a hierarchical model for temporal data, comprising:

receiving means for receiving a plurality of data streams comprising the temporal data;

mutual information means, configured to receive said plurality of data streams from said receiving means, for identifying a mutual information value between pairs of said data streams, said mutual information value representing the mutual information between said pair of data stream;

clustering means, configured to receive said mutual information values from said mutual information means, for clustering said data streams into at least two clusters based upon said mutual information;

hierarchical model means, configured to receive said clusters from said clustering means, for creating a current level of the hierarchical model based upon said clusters, wherein said current level generates additional data streams that are sent to the receiving means in order to start the process of creating additional levels of the hierarchical model.

8. The system of claim 7, wherein the hierarchical model represents a hierarchical temporal memory network.

9. The system of claim 7, wherein the step of creating a current level includes the step of creating a node for each cluster.

10. The system of claim 7, wherein said mutual information represents a correlation between pairs of said data streams.

11. The system of claim 7, wherein the data streams can be received from different levels of the hierarchical model.

12. The system of claim 7, wherein said mutual information is based upon at least one of spatial correspondence or temporal correspondence.