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 | |
| 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
Memristive hierarchical temporal memory. / Krestinskaya, Olga; Dolzhikova, Irina; James Pappachen, Alex.
Modeling and Optimization in Science and Technologies. Springer Verlag, 2020. p. 181-194 (Modeling and Optimization in Science and Technologies; Vol. 14).Research output: Chapter in Book/Report/Conference proceeding › Chapter
}
TY - CHAP
T1 - Memristive hierarchical temporal memory
AU - Krestinskaya, Olga
AU - Dolzhikova, Irina
AU - James Pappachen, Alex
PY - 2020/1/1
Y1 - 2020/1/1
N2 - 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.
AB - 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.
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UR - http://www.scopus.com/inward/citedby.url?scp=85064751517&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-14524-8_14
DO - 10.1007/978-3-030-14524-8_14
M3 - Chapter
AN - SCOPUS:85064751517
T3 - Modeling and Optimization in Science and Technologies
SP - 181
EP - 194
BT - Modeling and Optimization in Science and Technologies
PB - Springer Verlag
ER -