Memristors can implement fuzzy logic
Martin Klimo, Ondrej Such

TL;DR
This paper explores using memristors to implement fuzzy logic operations, demonstrating potential for computational circuits that can perform learning and classification tasks.
Contribution
It introduces memristor-based circuits for fuzzy logic, detailing their design, computational power, and experimental behavior, advancing memristor applications in fuzzy systems.
Findings
Memristor circuits can perform min and max operations for fuzzy logic.
Experimental memristor behavior supports learning capabilities.
Potential applications include fuzzy classifiers.
Abstract
In our work we propose implementing fuzzy logic using memristors. Min and max operations are done by antipodally configured memristor circuits that may be assembled into computational circuits. We discuss computational power of such circuits with respect to m-efficiency and experimentally observed behavior of memristive devices. Circuits implemented with real devices are likely to manifest learning behavior. The circuits presented in the work may be applicable for instance in fuzzy classifiers.
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Taxonomy
TopicsAdvanced Memory and Neural Computing · Neural dynamics and brain function · Neuroscience and Neural Engineering
