Review demonstrates that FPGA platforms reliably emulate memristor devices, highlighting viable pathways for neuromorphic computing systems.
This paper explores the field of FPGA implementation and emulation of memristor devices, providing insights into the advancements, challenges, and future directions.The paper discusses various techniques used for FPGA-based memristor emulation, emphasizing the importance of accurate memristor modeling and performance evaluation.It identifies challenges in the field, including improving accuracy, scalability, real-time adaptation, standardization, integration with design tools, and exploring novel applications.Additionally, the results of the study show that FPGAs are one of the viable solutions for emulating memristors.The study concludes that FPGA based memristor emulation holds a promise for studying memristor-based circuits and systems, with potential applications in neuromorphic computing, machine learning accelerators, and analog/mixed-signal circuit design.
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Aklah et al. (2024) studied this question.
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