Neuromodeling of microwave circuits exploiting space mapping technology

Space mapping (SM) technology based neuromodels decrease the cost of training, improve generalization ability and reduce the complexity of the ANN topology w.r.t. classical neuromodeling. Three novel techniques are proposed to generate SM based neuromodels: space-mapped neuromodeling (SMN), frequenc...

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Bibliographic Details
Main Authors: Bandler, J.W., Ismail, M.A., Rayas-Sanchez, J.E., Zhang, Q.J.
Format: Conference Proceeding
Language:English
Subjects:
Artificial neural networks
Circuit simulation
Circuit topology
Computational modeling
Frequency
Mathematical model
Microwave circuits
Microwave technology
Samarium
Space technology
Online Access:Request full text
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Summary:Space mapping (SM) technology based neuromodels decrease the cost of training, improve generalization ability and reduce the complexity of the ANN topology w.r.t. classical neuromodeling. Three novel techniques are proposed to generate SM based neuromodels: space-mapped neuromodeling (SMN), frequency dependent space-mapped neuromodeling (FDSMN), and frequency-space-mapped neuromodeling (FSMN). Huber optimization is proposed to train the neuro-space-mapping (NSM). The techniques are illustrated by a microstrip right angle bend.
ISSN:0149-645X
DOI:10.1109/MWSYM.1999.779445