Memristive hierarchical temporal memory

Olga Krestinskaya; Irina Dolzhikova; Alex James Pappachen

doi:10.1007/978-3-030-14524-8_14

Memristive hierarchical temporal memory

Olga Krestinskaya, Irina Dolzhikova, Alex James Pappachen

Department of Electrical and Computer Engineering

Research output: Chapter in Book/Report/Conference proceeding › Chapter

Abstract

This chapter covers the memristive HTM implementations on mixed-signal and analog hardware. Most of the implemented memristive systems are based on modified HTM algorithm. The HTM is often used as a feature encoding and feature extraction tool, and these features are then used with conventional nearest neighbor method for classification.

Original language	English
Title of host publication	Modeling and Optimization in Science and Technologies
Publisher	Springer Verlag
Pages	181-194
Number of pages	14
DOIs	https://doi.org/10.1007/978-3-030-14524-8_14
Publication status	Published - Jan 1 2020

Publication series

Name	Modeling and Optimization in Science and Technologies
Volume	14
ISSN (Print)	2196-7326
ISSN (Electronic)	2196-7334

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ASJC Scopus subject areas

Modelling and Simulation
Medical Assisting and Transcription
Applied Mathematics

Cite this

Krestinskaya, O., Dolzhikova, I., & James Pappachen, A. (2020). Memristive hierarchical temporal memory. In Modeling and Optimization in Science and Technologies (pp. 181-194). (Modeling and Optimization in Science and Technologies; Vol. 14). Springer Verlag. https://doi.org/10.1007/978-3-030-14524-8_14

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Access to Document

10.1007/978-3-030-14524-8_14