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April 22, 2026Open Access

Exploring temporal dynamics of TiOx-based memristors for optimised robustness in neuromorphic computing

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AWAlexander-Hanyu Wang

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Overview

Thesis investigates TiOx-based memristors for enhanced robustness in neuromorphic computing, indicating potential improvements in AI performance.

Key Points

  • This work aims to explore the use of TiOx-based memristors to enhance robustness in neuromorphic computing and mimic brain functionalities.
  • Investigated volatile and non-volatile TiOx-based memristors under pulse modulation
  • Analyzed the effects of oxygen flow rates on memristor composition and performance
  • Evaluated memristors' ability to perform memory tasks using the MNIST dataset
  • Volatile memristors demonstrated 90% accuracy in MNIST classification under ideal conditions
  • Non-volatile variants successfully supported long-term retention
  • Temporal dynamics showed that altered oxygen flow rates significantly affected memory performance.

Cite This Study

Alexander-Hanyu Wang (2026) studied this question.

synapsesocial.com/papers/69e866616e0dea528ddeaba0https://doi.org/10.5258/soton/pg/t168
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