The memristive artificial neuron high level architecture for biologically inspired robotic systems
- Resource Type
- Conference
- Authors
- Talanov, Max; Zykov, Evgeniy Yu.; Erokhin, Victor; Magid, Evgeni; Distefano, Salvatore
- Source
- 2017 International Conference on Mechanical, System and Control Engineering (ICMSC) Mechanical, System and Control Engineering (ICMSC), 2017 International Conference on. :196-200 May, 2017
- Subject
- Robotics and Control Systems
Robots
Neurons
Computer architecture
Memristors
Computational modeling
Biological system modeling
Cognitive architecture
memristive elements
circuits
artificial neuron
affects
biologically inspired robotic system
- Language
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.