Trust region‐based optimization of PKI neural models for RF/microwave devices |
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| Authors: | Lakshman Mareddy Mohammad Almalkawi Srinivasa Vemuru Mohamed Bakr Vijay Devabhaktuni |
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| Affiliation: | 1. EECS Department, University of Toledo, MS 308, 2801 W. Bancroft St., Toledo, OH 43606;2. ECCS Department, Ohio Northern University, Biggs 245, 525 South Main St., Ada, OH 45810;3. Department of Electrical and Computer Engineering, McMaster University, Hamilton, ON L8S 4K1, Canada |
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| Abstract: | This article proposes a new trust region‐based optimization technique for Radio Frequency (RF)/microwave devices. The proposed approach is apt for modeling scenarios, where standard ANN multilayer perceptron (MLP) and Prior Knowledge Input (PKI) models fail to deliver a satisfactory model. This approach feeds output of standard ANN model as knowledge input to PKI model. The ANN model and the PKI model form a symbiotic pair to yield accurate results. In this paper, the dogleg routine is exploited in the process of optimization to obtain valid trust region steps. The proposed method is compared with sensitivity technique via several RF/microwave components. © 2012 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2013. |
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| Keywords: | artificial neural networks device modeling dogleg optimization PKI models trust region |
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