Since CMOS technology approaches its physical limits, the spotlight of computing technologies and architectures shifts to unconventional computing approaches. In this area, novel computing systems, inspired by natural and mostly non-electronic approaches, provide also new ways of performing a wide range of computations, from simple logic gates to solving computationally hard problems. Reaction-diffusion processes constitute an information processing method, occurs in nature and are capable of massive parallel and low-power computing, such as chemical computing through Belousov-Zhabotinsky reaction. In this paper, inspired by these chemical processes and based on the wave-propagation information processing taking place in the reaction-diffusion media, the novel characteristics of the nanoelectronic element memristor are utilized to design innovative circuits of electronic excitable medium to perform both classical (Boolean) calculations and to model neuromorphic computations in the same Memristor-RLC (M-RLC) reconfigurable network.

Wave computing with passive memristive networks

Erokhin Victor;
2019

Abstract

Since CMOS technology approaches its physical limits, the spotlight of computing technologies and architectures shifts to unconventional computing approaches. In this area, novel computing systems, inspired by natural and mostly non-electronic approaches, provide also new ways of performing a wide range of computations, from simple logic gates to solving computationally hard problems. Reaction-diffusion processes constitute an information processing method, occurs in nature and are capable of massive parallel and low-power computing, such as chemical computing through Belousov-Zhabotinsky reaction. In this paper, inspired by these chemical processes and based on the wave-propagation information processing taking place in the reaction-diffusion media, the novel characteristics of the nanoelectronic element memristor are utilized to design innovative circuits of electronic excitable medium to perform both classical (Boolean) calculations and to model neuromorphic computations in the same Memristor-RLC (M-RLC) reconfigurable network.
2019
Istituto dei Materiali per l'Elettronica ed il Magnetismo - IMEM
978-1-7281-0397-6
CHEMICAL IMPLEMENTATION; CIRCUITS
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/374287
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