Memristive hierarchical temporal memory

Olga Krestinskaya, Irina Dolzhikova, Alex James Pappachen

Research output: Chapter in Book/Report/Conference proceedingChapter

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 languageEnglish
Title of host publicationModeling and Optimization in Science and Technologies
PublisherSpringer Verlag
Pages181-194
Number of pages14
DOIs
Publication statusPublished - Jan 1 2020

Publication series

NameModeling and Optimization in Science and Technologies
Volume14
ISSN (Print)2196-7326
ISSN (Electronic)2196-7334

    Fingerprint

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