TAILIEUCHUNG - A compact device model for nanoparticle-organic memory transistor’s characterization
Neuromorphic electronic devices have recently been a candidate for new computing architecture associated with innovative nanotechnologies. A report of the characterization of Nanoparticle organic memory transistor (NOMFET) introduced a similar behavior to a biological spiking synapse in neural networks. In this paper, a refinement model based on the extracted parameters including a hybrid NOMFET/CMOS neuromorphic computing circuit and architecture of synapse to neuron interface by characterizing transistor – memory and the temporal dynamic function is presented. | Communications in Physics, Vol. 28, No. 3 (2018), pp. 191-200 DOI: A COMPACT DEVICE MODEL FOR NANOPARTICLE-ORGANIC MEMORY TRANSISTOR’S CHARACTERIZATION MAI VAN HUYa,† OLIVIER BICHLERb , CHRISTIAN GAMRATb YANNICK VIEROc , FABIEN ALIBARTc AND DOMINIQUE VUILLAUMEc a Le Quy Don Technical University, 234 Hoang Quoc Viet, Bac Tu Liem, Hanoi, Vietnam b CEA LIST, 91191 Gif–sur-Yvette, France c Institute for Electronics Microelectronics and Nanotechnology (IEMN), CNRS, Univ. of Lille, CS 60069, 59652 Villeneuve d’ Ascq, France † E-mail: Received 23 April 2018 Accepted for publication 26 June 2018 Published 31 August 2018 Abstract. Neuromorphic electronic devices have recently been a candidate for new computing architecture associated with innovative nanotechnologies. A report of the characterization of Nanoparticle organic memory transistor (NOMFET) introduced a similar behavior to a biological spiking synapse in neural networks. In this paper, a refinement model based on the extracted parameters including a hybrid NOMFET/CMOS neuromorphic computing circuit and architecture of synapse to neuron interface by characterizing transistor – memory and the temporal dynamic function is presented. A compact EKV model refinement serves as a link between nanotechnology process and circuit design for novel CMOS devices. Keywords: dynamics, hybrid integrated circuit, modeling, nanotechnology, neural networks, synapse-like nanodevices, EKV model. Classification numbers: , . I. INTRODUCTION Neuromorphic electronics appears as a promising computing architecture to replace the traditional Von Neumann architecture. The spiking neural network (SNN) is a network model, which uses relative spike timing for information coding, inspires from how the brain works, to c 2018 Vietnam Academy of Science and Technology 192 MAI VAN HUY et al. allow fast and efficient information processing for complex tasks, such as recognition
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