Assessing the Impact of Defects on Energy Dissipation of QCA LT Gate using ML Models-Reference-Cited by-同舟云学术

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Assessing the Impact of Defects on Energy Dissipation of QCA LT Gate using ML Models

Published:2023-04-07 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE Devices for Integrated Circuit (DevIC)
language:
Short-container-title:

Author:

Dhar Manali¹,Mukherjee Chiradeep²,Manna Debasmita¹,Banerjee Ananya¹,Panda Saradindu³,Maji Bansibadan¹

Affiliation:

1. NIT Durgapur,Department of ECE,Durgapur,India

2. UEM Kolkata,Department of CST & CSIT,Kolkata,India

3. DSCSITSC,Department of ECE,Kolkata,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10134754/10134560/10134945.pdf?arnumber=10134945

Reference28 articles.

1. A Method of Majority Logic Reduction for Quantum Cellular Automata

2. A matrix representation method for decoders using majority gate characteristics in quantum-dot cellular automata

3. QCA-Based Nano Circuits Design

4. Machine Learning: Algorithms, Real-World Applications and Research Directions

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Predicting Energy Dissipation in QCA-Based Layered-T Gates Under Cell Defects and Polarisation: A Study with Machine-Learning Models;Journal of Electronic Testing;2024-08-21

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