HIERARCHICAL TEMPORAL MEMORY
including
HTM Cortical Learning Algorithms
VERSION 0.2.1, SEPTEMBER 12, 2011
©Numenta, Inc. 2011
Use of Numenta’s software and intellectual property, including the ideas contained in this document, are free for non-commercial research purposes. For details, see http://www.numenta.com/about-numenta/licensing.php.
ThisReadisThisa draftFirst!version of this document. There are several things missing that you should be aware of.
ThisWhatdocumentIS in thisdescribesdo ument:in detail new algorithms for learning and prediction developed by Numenta. The new algorithms are described in sufficient detail that a programmer can understand and implement them if desired. It starts with an introductory chapter. If you have been following Numenta and have read some of our past white papers, the material in the introductory chapter will be familiar. The other material is new.
ThereWhat isareNOTseveralin thistopicsdocument:related to the implementation of these new algorithms that did not make it into this early draft.
- Although most aspects of the algorithms have been implemented and tested in software, none of the test results are currently included.
- There is no description of how the algorithms can be applied to practical problems. Missing is a description of how you would convert data from a sensor or database into a distributed representation suitable for the algorithms.
- The algorithms are capable of on-line learning. A few details needed to fully implement on-line learning in some rarer cases are not described.
- Other planned additions include a discussion of the properties of sparse distributed representations, a description of applications and examples, and citations for the appendixes.
We are making this document available in its current form because we think the algorithms will be of interest to others. The missing components of the document should not impede understanding and experimenting with the algorithms by motivated researchers. We will revise this document regularly to reflect our progress.
© Numenta 2011 |
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Table of Contents
Preface
Chapter 1: HTM Overview
Chapter 2: HTM Cortical Learning Algorithms
Chapter 3: Spatial Pooling Implementation and Pseudocode Chapter 4: Temporal Pooling Implementation and Pseudocode
Appendix A: A Comparison between Biological Neurons and HTM Cells
Appendix B: A Comparison of Layers in the Neocortex and an HTM Region
Glossary
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© Numenta 2011 |
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