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A combination of FDTD and least‐squares support vector machines for analysis of microwave integrated circuits
Author(s) -
Yang Y.,
Hu S. M.,
Chen R. S.
Publication year - 2004
Publication title -
microwave and optical technology letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.304
H-Index - 76
eISSN - 1098-2760
pISSN - 0895-2477
DOI - 10.1002/mop.20615
Subject(s) - finite difference time domain method , support vector machine , microwave , realization (probability) , least squares support vector machine , electronic engineering , least squares function approximation , algorithm , computer science , statistical learning theory , engineering , machine learning , mathematics , telecommunications , statistics , optics , physics , estimator
This paper presents a new combination of the finite‐difference time‐domain (FDTD) method and the least‐squares support vector machines (LS‐SVM) technique. The LS‐SVM is a statistical‐learning method which has a self‐contained basis of statistical‐learning theory and excellent learning performance. A short segment of an FDTD record is used to train the LS‐SVM predictor in order to obtain an accurate future realization. Numerical simulations for two typical microwave filters demonstrate that the LS‐SVM method can achieve good forecasting accuracy and the efficiency of the FDTD method can be improved by up to 70%. © 2005 Wiley Periodicals, Inc. Microwave Opt Technol Lett 44: 296–299, 2005; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.20615