Device and System Co-Design of Summing Network With Floating Gate-Based Stochastic Neurons
The step-by-step scheme is proposed to co-design device and system architectural and operational parameters for the summing network with the floating gate-based stochastic neurons. In the proposed scheme, the input signal characteristics are first evaluated to determine the lowest possible error rat...
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| Format: | Article |
| Language: | English |
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IEEE
2025-01-01
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| Series: | IEEE Journal of the Electron Devices Society |
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| Online Access: | https://ieeexplore.ieee.org/document/10802866/ |
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| author | Akira Goda Chihiro Matsui Ken Takeuchi |
| author_facet | Akira Goda Chihiro Matsui Ken Takeuchi |
| author_sort | Akira Goda |
| collection | DOAJ |
| description | The step-by-step scheme is proposed to co-design device and system architectural and operational parameters for the summing network with the floating gate-based stochastic neurons. In the proposed scheme, the input signal characteristics are first evaluated to determine the lowest possible error rate. The size of the network is then determined to balance the error rate and the operating energy consumption. The device parameters such as device size and tunnel oxide thickness are set to achieve the desired response time of the neurons under the target input bias. As the source of stochasticity that realizes the stochastic resonance, the temporal noise (electron injection stochasticity (EIS) and random telegraph noise (RTN)), and the spatial distribution are analyzed. Among these three effects, EIS shows the most desirable characteristics for accurate and energy-efficient stochastic resonance operations. Furthermore, the effects of repeated cycling stress are evaluated to understand the reliability of the summing network as a system. In addition, the control scheme of the spatial threshold voltage variation is proposed. By following the proposed step-by-step design procedures, accurate, energy-efficient, and reliable operations of the summing network with the FG-based stochastic neurons can be realized. |
| format | Article |
| id | doaj-art-c413b3449119447f9cc9804c61ae805f |
| institution | Kabale University |
| issn | 2168-6734 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Journal of the Electron Devices Society |
| spelling | doaj-art-c413b3449119447f9cc9804c61ae805f2025-08-20T03:34:25ZengIEEEIEEE Journal of the Electron Devices Society2168-67342025-01-011366166810.1109/JEDS.2024.351765510802866Device and System Co-Design of Summing Network With Floating Gate-Based Stochastic NeuronsAkira Goda0https://orcid.org/0000-0002-7180-4925Chihiro Matsui1https://orcid.org/0000-0003-4594-6839Ken Takeuchi2https://orcid.org/0000-0002-9345-6503Department of Electrical Engineering and Information Systems, The University of Tokyo, Tokyo, JapanDepartment of Electrical Engineering and Information Systems, The University of Tokyo, Tokyo, JapanDepartment of Electrical Engineering and Information Systems, The University of Tokyo, Tokyo, JapanThe step-by-step scheme is proposed to co-design device and system architectural and operational parameters for the summing network with the floating gate-based stochastic neurons. In the proposed scheme, the input signal characteristics are first evaluated to determine the lowest possible error rate. The size of the network is then determined to balance the error rate and the operating energy consumption. The device parameters such as device size and tunnel oxide thickness are set to achieve the desired response time of the neurons under the target input bias. As the source of stochasticity that realizes the stochastic resonance, the temporal noise (electron injection stochasticity (EIS) and random telegraph noise (RTN)), and the spatial distribution are analyzed. Among these three effects, EIS shows the most desirable characteristics for accurate and energy-efficient stochastic resonance operations. Furthermore, the effects of repeated cycling stress are evaluated to understand the reliability of the summing network as a system. In addition, the control scheme of the spatial threshold voltage variation is proposed. By following the proposed step-by-step design procedures, accurate, energy-efficient, and reliable operations of the summing network with the FG-based stochastic neurons can be realized.https://ieeexplore.ieee.org/document/10802866/Stochastic neuronfloating gatesumming networkstochastic resonanceinter-spike intervalleaky-integrate and fire |
| spellingShingle | Akira Goda Chihiro Matsui Ken Takeuchi Device and System Co-Design of Summing Network With Floating Gate-Based Stochastic Neurons IEEE Journal of the Electron Devices Society Stochastic neuron floating gate summing network stochastic resonance inter-spike interval leaky-integrate and fire |
| title | Device and System Co-Design of Summing Network With Floating Gate-Based Stochastic Neurons |
| title_full | Device and System Co-Design of Summing Network With Floating Gate-Based Stochastic Neurons |
| title_fullStr | Device and System Co-Design of Summing Network With Floating Gate-Based Stochastic Neurons |
| title_full_unstemmed | Device and System Co-Design of Summing Network With Floating Gate-Based Stochastic Neurons |
| title_short | Device and System Co-Design of Summing Network With Floating Gate-Based Stochastic Neurons |
| title_sort | device and system co design of summing network with floating gate based stochastic neurons |
| topic | Stochastic neuron floating gate summing network stochastic resonance inter-spike interval leaky-integrate and fire |
| url | https://ieeexplore.ieee.org/document/10802866/ |
| work_keys_str_mv | AT akiragoda deviceandsystemcodesignofsummingnetworkwithfloatinggatebasedstochasticneurons AT chihiromatsui deviceandsystemcodesignofsummingnetworkwithfloatinggatebasedstochasticneurons AT kentakeuchi deviceandsystemcodesignofsummingnetworkwithfloatinggatebasedstochasticneurons |