Advanced Neural Network Techniques for GaN-HEMT Dynamic Behavior Characterization

This paper presents a new approach to build RF dynamic behavioral models, based on time-delay neural networks (TDNNs), suitable for FET devices, and capable to identify the working class and to characterize both short- and long-term device memory, through a time-domain training procedure, for a wide...

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Bibliographic Details
Published in2006 European Microwave Integrated Circuits Conference pp. 249 - 252
Main Authors Orengo, G., Colantonio, P., Giannini, F., Pirola, M., Camarchia, V., Guerrieri, S.D.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.09.2006
Subjects
Delay effects
Dynamic behavioral model
Finite impulse response filter
GaN
Intrusion detection
Network synthesis
Neural Network
Neural networks
Neurons
Nonlinear filters
Radio frequency
Sampling methods
Thermal model
Time domain analysis
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Summary:This paper presents a new approach to build RF dynamic behavioral models, based on time-delay neural networks (TDNNs), suitable for FET devices, and capable to identify the working class and to characterize both short- and long-term device memory, through a time-domain training procedure, for a wide range of input power levels. The presented model has been effectively applied to GaN-based devices, working in class A, AB and B
ISBN:9782960055184
2960055187
DOI:10.1109/EMICC.2006.282799