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MatlabHTM: A sequence memory model of neocortical layers for anomaly detection

Authors :
Ilia Bautista
Sudeep Sarkar
Sanjukta Bhanja
Source :
SoftwareX, Vol 11, Iss , Pp - (2020)
Publication Year :
2020
Publisher :
Elsevier, 2020.

Abstract

Many models based on the operation of the neocortex, which is the center of brain intelligence, are emerging. The Hierarchical Temporal Memory (HTM) model is a unique intermediate level model of the neocortex’s layered substructures. The hypothesis is that these layers build temporal models of sequences of observations and/or motor signals, i.e., build a sequence memory. Implementations of this model exist in Python, C++ and Java. However, those implementations are quite cumbersome to use, as they depend on many other packages. This paper presents a lean, standalone, easy to modify MATLAB implementation. The performance results from processing the Numenta Anomaly Benchmark (NAB) demonstrate the fidelity of matlabHTM.

Details

Language :
English
ISSN :
23527110
Volume :
11
Issue :
-
Database :
Directory of Open Access Journals
Journal :
SoftwareX
Publication Type :
Academic Journal
Accession number :
edsdoj.8278eb4d5e9440acaae635a24ab28c29
Document Type :
article
Full Text :
https://doi.org/10.1016/j.softx.2020.100491