Design A KL-Band Power Divider Using EC-ANN Models for BGCPW Discontinuities

Novel accurate and efficient equivalent circuit trained artificial neural-network (EC-ANN) models, which inherit and develop EC model and EM-ANN model's advantages, have been developed for back-grounded coplanar waveguide (BGCPW) discontinuities. Modeled discontinuities include BGCPW bend and B...

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Bibliographic Details
Main Authors: Hu Jiang, Sun Lingling, Xu Ruimin
Format: Conference Proceeding
Language:English
Subjects:
artificial neural-network
BGCPW
Circuit simulation
Circuit synthesis
Circuit testing
Coplanar waveguides
Design automation
Design optimization
discontinuities
equivalent circuit
Equivalent circuits
Performance evaluation
power divider
Power dividers
Waveguide discontinuities
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Summary:Novel accurate and efficient equivalent circuit trained artificial neural-network (EC-ANN) models, which inherit and develop EC model and EM-ANN model's advantages, have been developed for back-grounded coplanar waveguide (BGCPW) discontinuities. Modeled discontinuities include BGCPW bend and BGCPW symmetric T-junction, for which the validation tests are performed. These models allow for circuit design, simulation, and optimization within CAD simulator. A KL-band 4dB power divider on GaAs substrate is designed using the developed BGCPW EC-ANN models.
ISSN:2325-0631
DOI:10.1109/ISICIR.2007.4441788