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Programmable Neuromorphic Circuit based on Printed Electrolyte-Gated Transistors

  • Neuromorphic computing systems have demonstrated many advantages for popular classification problems with significantly less computational resources. We present in this paper the design, fabrication and training of a programmable neuromorphic circuit, which is based on printed electrolytegated field-effect transistor (EGFET). Based on printable neuron architecture involving several resistors andNeuromorphic computing systems have demonstrated many advantages for popular classification problems with significantly less computational resources. We present in this paper the design, fabrication and training of a programmable neuromorphic circuit, which is based on printed electrolytegated field-effect transistor (EGFET). Based on printable neuron architecture involving several resistors and one transistor, the proposed circuit can realize multiply-add and activation functions. The functionality of the circuit, i.e. the weights of the neural network, can be set during a post-fabrication step in form of printing resistors to the crossbar. Besides the fabrication of a programmable neuron, we also provide a learning algorithm, tailored to the requirements of the technology and the proposed programmable neuron design, which is verified through simulations. The proposed neuromorphic circuit operates at 5V and occupies 385mm 2 of area.‚Ķshow moreshow less

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Metadaten
Author:Dennis D. Weller, Michael Hefenbrock, Mehdi Baradaran Tahoori, Jasmin Aghassi-HagmannORCiDGND, Michael Beigl
Creating Corporation:IEEE
Year of Publication:2020
ISBN:978-1-7281-4123-7 (eBook)
ISBN:978-1-7281-4124-4 (Print on Demand)
Language:English
Parent Title (English):2020 25th Asia and South Pacific Design Automation Conference (ASP-DAC) : Proceedings
ISSN:2153-697X (Online)
ISSN:2153-6961 (Print on Demand)
First Page:446
Last Page:451
Document Type:Conference Proceeding
Institutes:Bibliografie
Acces Right:Zugriffsbeschränkt
Release Date:2020/12/16
Licence (German):License LogoEs gilt das UrhG
Note:
Konferenz: 2020 25th Asia and South Pacific Design Automation Conference (ASP-DAC), 13-16 Jan. 2020, Beijing, China
DOI:https://doi.org/10.1109/ASP-DAC47756.2020.9045211