Tian, Mengyue, Bell, James J. ![]() ![]() ![]() ![]() |
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Abstract
This article introduces a novel artificial neural network (ANN) structure determination process based on the Cardiff model (CM), to determine ANN-based transistor nonlinear behavioral models. By relating the CM formulation and coefficients to the Taylor series expansion of the ANN model, a novel approach for determining the required values of a fully connected cascaded (FCC) ANN structure has been formulated. The proposed method provides the chance to escape from the possible time-consuming ANN determination process. Experiments proved that the proposed ANN models using the determination method can provide accurate prediction for the behavior acquired from load–pull characterizations of a Wolfspeed 10-W packaged gallium nitride (GaN) high electron mobility transistor (HEMT) simulation at 3.5 GHz, and a dense load–pull measurement of WIN NP12 4 × 75 μ m GaN HEMT at 20 GHz, with normalized mean square error (NMSE) levels lower than − 40 dB.
Item Type: | Article |
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Date Type: | Published Online |
Status: | In Press |
Schools: | Engineering |
Publisher: | Institute of Electrical and Electronics Engineers |
ISSN: | 0018-9480 |
Date of First Compliant Deposit: | 23 July 2024 |
Date of Acceptance: | 19 July 2024 |
Last Modified: | 07 Nov 2024 13:45 |
URI: | https://orca.cardiff.ac.uk/id/eprint/170863 |
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