Talks and Poster Presentations (with Proceedings-Entry):
N. TaheriNejad, S. Pudukotai Dinakarrao, A. Jantsch:
"Memristors' Potential for Multi-Bit Storage and Pattern Learning";
Talk: IEEE Proceeding of the 9th European Modelling Symposium (EMS 2015),
Madrid, Spain;
2015-10-06
- 2015-10-08; in: "IEEE Proceedings of the 9th European Modelling Symposium (EMS 2015)",
Madrid, Spain
(2015),
ISBN: 978-1-5090-0206-1;
6 pages.
English abstract:
Memristor is a two-terminal device, termed as fourth element, and characterized by a varying resistance depending on the charge (current) flown through it. This leads to many interesting characteristics, including a memory of its past states, demonstrated in its resistance. Smaller area and power consumed by memristors compared to conventional memories makes them a more suitable choice for applications needing large memory. In this paper we explore one of the unique properties of memristors which extends their suitability by allowing storage of multi-bit data in a single memristor. Their ability of storing multi-bit patterns will be shown via a simplified proof and simulations. This characteristic can be advantageous for many applications. In this paper particularly, we briefly discuss its advantages in pattern learning applications.
Keywords:
memristors;pattern recognition;random-access storage;memristors;multibit data storage;pattern learning;two-terminal device;Batteries;Encoding;Memory management;Memristors;Pattern recognition;Resistance;Switches;Digital Coding Systems;Memristors;Multi-bit
"Official" electronic version of the publication (accessed through its Digital Object Identifier - DOI)
http://dx.doi.org/10.1109/EMS.2015.73
Electronic version of the publication:
http://publik.tuwien.ac.at/files/publik_244029.pdf
Created from the Publication Database of the Vienna University of Technology.