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The memristive artificial neuron high level architecture for biologically inspired robotic systems

Max Talanov, E. Yu. Zykov, Victor Erokhin, Evgeni Magid, Salvatore Distefano

Year
2017
Citations
6

Abstract

In this paper we propose a new hardware architecture for the implementation of an artificial neuron based on organic memristive elements and operational amplifiers. This architecture is proposed as a possible solution for the integration and deployment of the cluster based bio- realistic simulation of a mammalian brain into a robotic system. Originally, this simulation has been developed through a neuro-biologically inspired cognitive architecture (NeuCogAr) re-implementing basic emotional states or affects in a computational system. This way, the dopamine, serotonin and noradrenaline pathways developed in NeuCogAr are synthesized through hardware memristors suitable for the implementation of basic emotional states or affects on a biologically inspired robotic system.

Keywords

MemristorComputer scienceArchitectureComputer architectureSoftware deploymentBiomimeticsArtificial intelligenceCognitive architectureEmbedded systemCognition

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