Theses and Dissertations
Date of Award
12-2024
Document Type
Thesis
Degree Name
M.S.
Department
Electrical and Computer Engineering
Committee Chair
Jinhui Wang
Abstract
A three-dimensional neuromorphic (3D) computing architecture based on environmentally sustainable natural organic honey memristors is proposed in this thesis. A set of comprehensive and experimental results indicate that the proposed systems exhibit remarkable inference accuracy, consistently surpassing the 90% threshold, even with different challenges such as device variations and nonlinearity. This study also considers four different conductance drift situations, the effects of analog-to-digital converter (ADC) quantization, and multiple algorithms, such as VGG8 and DenseNet-40. The deliverable of this thesis will test the stability of the proposed systems and explore their potential applications and scalability in real-world situations.
Recommended Citation
Khan, Mohammed Rafeeq, "Three-Dimensional Environmentally Sustainable Neuromorphic Computing System Based on Natural Organic Memristor" (2024). Theses and Dissertations. 209.
https://jagworks.southalabama.edu/theses_diss/209
Included in
Electrical and Electronics Commons, Other Computer Engineering Commons, Other Electrical and Computer Engineering Commons
