Enhancement of time domain analysis and optimization through neural networks

Authors

  • Hong-Son Chu,

    1. Computational Electromagnetics Research Laboratory, Department of Electrical and Computer Engineering, University of Victoria, Victoria, BC, Canada, V8W 3P6
    2. Computational Electromagnetics and Electronics Division, Institute of High Performance Computing, 1 Science Park Road, no. 01-01 the Capricorn Singapore Science Park II, Singapore 117528
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  • Wolfgang J. R. Hoefer

    Corresponding author
    1. Computational Electromagnetics Research Laboratory, Department of Electrical and Computer Engineering, University of Victoria, Victoria, BC, Canada, V8W 3P6
    • Computational Electromagnetics Research Laboratory, Department of Electrical and Computer Engineering, University of Victoria, Victoria, BC, Canada, V8W 3P6
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Abstract

An efficient computational approach to time domain microwave design and optimization is presented. In particular, artificial neural networks are coupled with a full-wave time domain simulator in order to model and optimize microwave structures. Furthermore, neural networks are used to predict the late time response from the early time response of a structure to accelerate the convergence of time domain simulations, particularly in the case of high-Q structures such as filters and resonators. The combination of neural networks with a time domain TLM solver is demonstrated by means of a design example of an iris-coupled band pass filter. The results demonstrate the dramatic gain in speed and numerical efficiency enabled by this approach to optimizing and modeling microwave devices. © 2007 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2007.

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