We present an integrated reconfigurable neuromorphic platform interfacing a selector-less 16x16 RRAM memristor crossbar array with peripheral row and column ...
Jul 5, 2024 · The introduced approach works in three phases, fault tolerance analysis, high-level fault detection, and low-level fault detection. In the first ...
Bio-plausible Learning-on-Chip with Selector-less Memristive Crossbars. JH Kim, S Jain, G Hota, J Park, A Kumar, D Kuzum, G Cauwenberghs. 2024 IEEE ...
Publication: Bio-plausible Learning-on-Chip with Selector-less ...
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Bio-plausible Learning-on-Chip with Selector-less Memristive Crossbars. Jeong-Hoon Kim Soumil Jain Gopabandhu Hota Jaeseoung Park Ashwani Kumar Duygu Kuzum ...
Bio-plausible Learning-on-Chip with Selector-less Memristive Crossbars. JH Kim, S Jain, G Hota, J Park, A Kumar, D Kuzum, G Cauwenberghs. 2024 IEEE ...
For hardware implementation with RRAM crossbar arrays, we developed a neuromorphic compute-in-memory platform (Fig. 5d). It utilizes a switched capacitor ...
2445 · 14.18, Bio-Plausible Learning-on-Chip with Selector-Less Memristive Crossbars Jeong-Hoon Kim, Soumil Jain, Gopabandhu Hota, Jaeseoung Park, Ashwani Kumar ...
Dec 15, 2023 · In this work, we studied Gd 0.3 Ca 0.7 MnO 3 (GCMO)-based memristive devices comprised of an asymmetrical electrode configuration, Al/GCMO/Au.
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Dec 29, 2022 · This work explores the interrelationship of implementing bio-plausible learning in-situ on neuromorphic hardware, emphasizing energy, area, and latency ...
Missing: Selector- less Memristive Crossbars.
Jun 3, 2022 · The proposed highly reliable memristor can be broadly used in neuromorphic processors that handle bio-plausible neural networks. Further ...