Memristor Cellular Nonlinear Networks

Angela Slavova () and Ventsislav Ignatov
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Angela Slavova: Institute of Mathematics and Informatics, Bulgarian Academy of Sciences, 1113 Sofia, Bulgaria
Ventsislav Ignatov: Laboratory of Engineering Mathematics, Ruse University “Angel Kanchev”, 7017 Ruse, Bulgaria

Mathematics, 2023, vol. 11, issue 7, 1-19

Abstract: This paper presents a review of the theory and applications of memristor cellular nonlinear networks. By mapping the physical processes to the memristive framework, all resistive switching devices can be modeled. The idea is to find a state variable that presents with high accuracy the important features of the system, its dynamics, and time evolution in response to the inputs of the memristor. In order to develop a new design of memristor-based cellular nonlinear networks (MCNN), new circuital and mathematical memristor models need to be introduced. In this way, implementation into new software packages for computer-aided integrated circuit realization can be achieved. Another challenging problem is studying the complex behavior of MCNN models by means of local activity theory and generalizing it for various test cases. An application of the hardware implementation of these models can be found in nanostructures.

Keywords: memristor; cellular nonlinear networks; memristor cellular nonlinear networks; pattern formation (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
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