Memristor Crossbar-based Hardware Implementation of IDS Method

Abstract

Ink Drop Spread (IDS) is the engine of Active Learning Method (ALM), which is the methodology of soft computing. IDS, as a pattern-based processing unit, extracts useful information from a system subjected to modeling. In spite of its excellent potential in solving problems such as classification and modeling compared to other soft computing tools, finding its simple and fast hardware implementation is still a challenge. This paper describes a new hardware implementation of IDS method based on the memristor crossbar structure. In addition of simplicity, being completely real-time, having low latency and the ability to continue working after the occurrence of power breakdown are some of the advantages of our proposed circuit.

16 pages, 13 figures, Submitted to IEEE Transaction on Fuzzy Systems

References in corpus (2)

• Practical approach to programmable analog circuits with memristors
• Memristive model of amoeba's learning

Cited by in corpus (5)

• Neuro-Fuzzy Computing System with the Capacity of Implementation on Memristor-Crossbar and Optimization-Free Hardware Training
• Bottleneck of using single memristor as a synapse and its solution
• Fast IDS Computing System Method and its Memristor Crossbar-based Hardware Implementation
• Efficient neuro-fuzzy system and its Memristor Crossbar-based Hardware Implementation
• Circuit proposition for copying the value of a resistor into a memristive device supported by HSPICE simulation