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MatlabHTM: A sequence memory model of neocortical layers for anomaly detection
- 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.
- Subjects :
- Neural modeling
Sequence memory
HTM
Computer software
QA76.75-76.765
Subjects
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