Implementation efficiency comparison between ANN and the Cardiff Model in ADS

Yuan, Weihao ORCID: https://orcid.org/0000-0001-9857-574X, Tian, Mengyue and Bell, James ORCID: https://orcid.org/0000-0002-4815-2199 2023. Implementation efficiency comparison between ANN and the Cardiff Model in ADS. Presented at: 2023 International Workshop on Integrated Nonlinear Microwave and Millimeterwave Circuits, INMMIC, 08-11 November 2023. 2023 International Workshop on Integrated Nonlinear Microwave and Millimetre-Wave Circuits (INMMIC). IEEE, pp. 1-4. 10.1109/INMMIC57329.2023.10321776

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Abstract

This paper presents CAD implementations of the Artificial Neural Network (ANN) model and the Cardiff Model (CM) in Keysight Advanced Design System (ADS). A comparative analysis of running time difference between the two behavioral models is conducted. The results indicate that the removal of certain dispensable calculations in the CM template can save 99% of time on large dataset simulations at the fundamental frequency, while maintaining a Normalized Mean Square Error (NMSE) level lower than -50 dB. The modified CM exhibits a similar runtime compared to the ANN model with selected structure. This paper also explores the impact of changing the number of the CM coefficients and hidden neurons in the ANN model on the simulation time in ADS at fundamental frequency, without considering the accuracy of models. Results reveal a linear relationship between the simulation time and the number of the hidden neurons in the ANN model whereas the simulation time of the CM is more related to the exponents for |a 2,1 |.

Item Type:	Conference or Workshop Item (Paper)
Date Type:	Published Online
Status:	Published
Schools:	Engineering
Publisher:	IEEE
ISBN:	979-8-3503-2242-2
Last Modified:	08 Jan 2024 09:30
URI:	https://orca.cardiff.ac.uk/id/eprint/164765

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