A fully analog CMOS implementation of a two-variable spiking neuron in the subthreshold region and its network operation
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10.1109/IJCNN55064.2022.9891920
Inclou dades d'ús des de 2022
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hdl:2117/379255
Tipus de documentText en actes de congrés
Data publicació2022
EditorInstitute of Electrical and Electronics Engineers (IEEE)
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Abstract
Edge computing requires the processing of real-time and personalized information with low power consumption. Neuromorphic devices are promising candidates for applications related to edge computing. Rate neurons, which are typically used in neuromorphic hardware, persistently consume power regardless of their outputs. To further reduce the power consumption of neuromorphic devices, spiking neurons are more suitable because they are event-driven, and information is transferred only when the neuron fires. Herein, we propose a two-variable spiking neuron circuit that operates in a fully analog manner by utilizing the physical properties of transistors as analog devices. By operating in the subthreshold region of the MOS transistor, the energy required to produce a spike is approximately tens of fJ/spike. Furthermore, the analog neuron can exhibit complex spike dynamics, such as chattering, as confirmed using post-layout simulations. The simulations indicated that a neural network comprising the proposed neuron circuits operates successfully and exhibits complex nonlinear behavior. These results provide a basis for dedicated hardware spiking neuron circuits, which could be used as ultra-low-power neuromorphic hardware in various applications, such as realizing liquid-state machines for processing time-series signals. © 2022 IEEE.
Descripció
© 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
CitacióMoriya, S. [et al.]. A fully analog CMOS implementation of a two-variable spiking neuron in the subthreshold region and its network operation. A: International Joint Conference on Neural Networks. "2022 International Joint Conference on Neural Networks (IJCNN): Padua, Italy: July 18-23, 2022: proceedings". Institute of Electrical and Electronics Engineers (IEEE), 2022, p. 1-7. ISBN 978-1-7281-8671-9. DOI 10.1109/IJCNN55064.2022.9891920.
ISBN978-1-7281-8671-9
Versió de l'editorhttps://ieeexplore.ieee.org/document/9891920
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A_Fully_Analog_ ... _its_Network_Operation.pdf | 968,8Kb | Accés restringit |