Vol. 92
Latest Volume
All Volumes
PIER 180 [2024] PIER 179 [2024] PIER 178 [2023] PIER 177 [2023] PIER 176 [2023] PIER 175 [2022] PIER 174 [2022] PIER 173 [2022] PIER 172 [2021] PIER 171 [2021] PIER 170 [2021] PIER 169 [2020] PIER 168 [2020] PIER 167 [2020] PIER 166 [2019] PIER 165 [2019] PIER 164 [2019] PIER 163 [2018] PIER 162 [2018] PIER 161 [2018] PIER 160 [2017] PIER 159 [2017] PIER 158 [2017] PIER 157 [2016] PIER 156 [2016] PIER 155 [2016] PIER 154 [2015] PIER 153 [2015] PIER 152 [2015] PIER 151 [2015] PIER 150 [2015] PIER 149 [2014] PIER 148 [2014] PIER 147 [2014] PIER 146 [2014] PIER 145 [2014] PIER 144 [2014] PIER 143 [2013] PIER 142 [2013] PIER 141 [2013] PIER 140 [2013] PIER 139 [2013] PIER 138 [2013] PIER 137 [2013] PIER 136 [2013] PIER 135 [2013] PIER 134 [2013] PIER 133 [2013] PIER 132 [2012] PIER 131 [2012] PIER 130 [2012] PIER 129 [2012] PIER 128 [2012] PIER 127 [2012] PIER 126 [2012] PIER 125 [2012] PIER 124 [2012] PIER 123 [2012] PIER 122 [2012] PIER 121 [2011] PIER 120 [2011] PIER 119 [2011] PIER 118 [2011] PIER 117 [2011] PIER 116 [2011] PIER 115 [2011] PIER 114 [2011] PIER 113 [2011] PIER 112 [2011] PIER 111 [2011] PIER 110 [2010] PIER 109 [2010] PIER 108 [2010] PIER 107 [2010] PIER 106 [2010] PIER 105 [2010] PIER 104 [2010] PIER 103 [2010] PIER 102 [2010] PIER 101 [2010] PIER 100 [2010] PIER 99 [2009] PIER 98 [2009] PIER 97 [2009] PIER 96 [2009] PIER 95 [2009] PIER 94 [2009] PIER 93 [2009] PIER 92 [2009] PIER 91 [2009] PIER 90 [2009] PIER 89 [2009] PIER 88 [2008] PIER 87 [2008] PIER 86 [2008] PIER 85 [2008] PIER 84 [2008] PIER 83 [2008] PIER 82 [2008] PIER 81 [2008] PIER 80 [2008] PIER 79 [2008] PIER 78 [2008] PIER 77 [2007] PIER 76 [2007] PIER 75 [2007] PIER 74 [2007] PIER 73 [2007] PIER 72 [2007] PIER 71 [2007] PIER 70 [2007] PIER 69 [2007] PIER 68 [2007] PIER 67 [2007] PIER 66 [2006] PIER 65 [2006] PIER 64 [2006] PIER 63 [2006] PIER 62 [2006] PIER 61 [2006] PIER 60 [2006] PIER 59 [2006] PIER 58 [2006] PIER 57 [2006] PIER 56 [2006] PIER 55 [2005] PIER 54 [2005] PIER 53 [2005] PIER 52 [2005] PIER 51 [2005] PIER 50 [2005] PIER 49 [2004] PIER 48 [2004] PIER 47 [2004] PIER 46 [2004] PIER 45 [2004] PIER 44 [2004] PIER 43 [2003] PIER 42 [2003] PIER 41 [2003] PIER 40 [2003] PIER 39 [2003] PIER 38 [2002] PIER 37 [2002] PIER 36 [2002] PIER 35 [2002] PIER 34 [2001] PIER 33 [2001] PIER 32 [2001] PIER 31 [2001] PIER 30 [2001] PIER 29 [2000] PIER 28 [2000] PIER 27 [2000] PIER 26 [2000] PIER 25 [2000] PIER 24 [1999] PIER 23 [1999] PIER 22 [1999] PIER 21 [1999] PIER 20 [1998] PIER 19 [1998] PIER 18 [1998] PIER 17 [1997] PIER 16 [1997] PIER 15 [1997] PIER 14 [1996] PIER 13 [1996] PIER 12 [1996] PIER 11 [1995] PIER 10 [1995] PIER 09 [1994] PIER 08 [1994] PIER 07 [1993] PIER 06 [1992] PIER 05 [1991] PIER 04 [1991] PIER 03 [1990] PIER 02 [1990] PIER 01 [1989]
2009-04-15
Knowledge-Based Support Vector Synthesis of the Microstrip Lines
By
Progress In Electromagnetics Research, Vol. 92, 65-77, 2009
Abstract
In this paper, we proposed an efficient knowledge-based Support Vector Regression Machine (SVRM) method and applied it to the synthesis of the transmission lines for the microwave integrated circuits, with the highest possible accuracy using the fewest accurate data. The technique has integrated advanced concepts of SVM and knowledge-based modeling into a powerful and systematic framework. Thus, synthesis model as fast as the coarse models and at the same time as accurate as the fine models is obtained for the RF/Microwave planar transmission lines. The proposed knowledge-based support vector method is demonstrated by a typical worked example of microstrip line. Success of the method and performance of the resulted synthesis model is presented and compared with ANN results.
Citation
Nurhan Türker Tokan, and Filiz Gunes, "Knowledge-Based Support Vector Synthesis of the Microstrip Lines," Progress In Electromagnetics Research, Vol. 92, 65-77, 2009.
doi:10.2528/PIER09022704
References

1. Zhang, Q. J. and K. C. Gupta, Neural Networks for RF and Microwave Design, Artech House, Norwood, MA, 2000.

2. Vapnik, V., The Nature of Statistical Learning Theory, Springer-Verlag, New York, 1995.

3. Bermani, E., A. Boni, A. Kerhet, and A. Massa, "Kernels evaluation of SVM based estimatiors for inverse scattering problems," Progress In Electromagnetics Research, PIER 53, 167-188, 2005.

4. Gunes, F., N. T. Tokan, and F. Gurgen, "Signal-noise support vector model of a microwave transistor," Int. J. RF and Microwave CAE, Vol. 17, 404-415, 2007.
doi:10.1002/mmce.20239

5. Gunes, F., N. T. Tokan, and F. Gurgen, "Support vector design of the microstrip lines," Int. J. RF and Microwave CAE, Vol. 18, 326-336, 2008.
doi:10.1002/mmce.20290

6. Tokan, N. T. and F. Gunes, "Support vector characterisation of resonance frequencies of microstrip antennas based on measurements," Progress In Electromagnetics Research B, Vol. 5, 49-51, 2008.
doi:10.2528/PIERB08013006

7. Wang, F. and Q. J. Zhang, "Knowledge-based neural models for microwave design," IEEE Trans. Microwave Theory Tech., Vol. 45, 2333-2343, Dec. 1997.
doi:10.1109/22.643839

8. Watson, P. M., K. C. Gupta, and R. L. Mahajan, "Applications of knowledge-based artificial neural network modeling to microwave components," Int. J. RF Microwave Computer-aided Eng., Vol. 9, 254-260, 1999.
doi:10.1002/(SICI)1099-047X(199905)9:3<254::AID-MMCE9>3.0.CO;2-G

9. Jargon, J. A., K. C. Gupta, and D. C. DeGroot, "Applications of artificial neural networks to RF and microwave measurements," Int. J. RF Microwave Computer-aided Eng., Vol. 12, 3-24, 2002.
doi:10.1002/mmce.10014

10. Bandler, J. W., M. A. Ismail, J. E. Rayas-Sanchez, and Q. J. Zhang, "Neuromodeling of microwave circuits exploiting space-mapping technology," IEEE Trans. Microwave Theory Tech., Vol. 47, 2417-2427, Dec. 1999.
doi:10.1109/22.808989

11. Bakr, M. H., J. W. Bandler, M. A. Ismail, J. E. Rayas-Sanchez, and Q. J. Zhang, "Neural space-mapping optimization for EM-based design," IEEE Trans. Microwave Theory Tech., Vol. 48, 2307-2315, Dec. 2000.
doi:10.1109/22.898979

12. Devabhaktuni, V. K., M. C. E. Yagoub, and Q. J. Zhang, "A robust algorithm for automatic development of neural network models for microwave applications," IEEE Trans. Microwave Theory Tech., Vol. 49, 2282-2291, Dec. 2001.
doi:10.1109/22.971611

13. Bandler, J. W., J. E. Rayas-Sanchez, and Q. J. Zhang, "Yielddriven electromagnetic optimization via space mapping-based neuromodels," Int. J. RF Microwave Computer-aided Eng., Vol. 12, 79-89, 2002.
doi:10.1002/mmce.10015

14. Devabhaktuni, V. K., B. Chattaraj, M. C. E. Yagoub, and Q. J. Zhang, "Advanced microwave modeling framework exploiting automatic model generation, knowledge neural networks, and space mapping," IEEE Trans. Microwave Theory Tech., Vol. 51, No. 7, 1822-1833, Jul. 2003.
doi:10.1109/TMTT.2003.814318

15. Edwards, T. C., "Foundations for microstrip circuit design,", Wiley-Interscience, New York, 1981.