A transfer learning approach to expedite training of artificial neural networks for variability-a...

Artificial Neural Networks With Fast Transfer Learning for Statistical Signal Integrity Analysis of MWCNT and MLGNR Interconnect Networks

S Guglani, AK Jakhar, K Dimple… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
In this article, artificial neural network (ANN) metamodels have been developed for the fast
statistical signal integrity analysis of multiwalled carbon nanotube and multilayer graphene …
被引用次数：2 相关文章

An Analytic RLC Model for Coupled Interconnects Which Uses a Numerical Inverse Laplace Transform

M Keran, A Dounavis - IEEE Transactions on Very Large Scale …, 2023 - ieeexplore.ieee.org
In this article, a numerical inverse Laplace transform (NILT)-based algorithm is used to
efficiently approximate key characteristics of coupled high-speed VLSI interconnects, such …
被引用次数：2 相关文章 所有 4 个版本

Prior knowledge accelerated transfer learning (PKI-TL) for machine learning assisted uncertainty quantification of MLGNR interconnect networks

AK Jakhar, S Guglani, A Dasgupta… - 2023 IEEE 32nd …, 2023 - ieeexplore.ieee.org
In this paper, an algorithm to combine the distinct advantages of knowledge-based training
and transfer learning has been developed for the fast artificial neural network (ANN) …
被引用次数：3 相关文章

Combining Prior Knowledge with Transfer Learning (PKID-TL) for Fast Neural Network Enabled Uncertainty Quantification of Graphene On-Chip Interconnects

S Guglani, AK Jakhar, A Dasgupta… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
In this paper, an artificial neural network (ANN) enabled uncertainty quantification technique
is developed for graphene on-chip interconnects. In the proposed technique, primary ANNs …
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A Fast Metalearning Algorithm for Neural Network Enabled Uncertainty Quantification of Graphene Based Interconnects with Passive Shielding

AK Jakhar, D Basu, K Dimple, S Guglani… - … , Signal & Power …, 2024 - ieeexplore.ieee.org
Inserting passive shield lines in between the active and victim conductors has become a
standard approach for mitigating the crosstalk effects in multi-walled carbon nanotube …
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Noise-Aware Uncertainty Quantification of MLGNR Interconnects using Fast Trained Artificial Neural Networks

AK Jakhar, S Guglani, A Dasgupta… - 2023 IEEE Electrical …, 2023 - ieeexplore.ieee.org
This paper presents a prior knowledge accelerated transfer learning technique to efficiently
train artificial neural networks (ANNs) to address uncertainty in on-chip multilayer graphene …
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