Department of Electronics and Communication Engineering
National Institute of Technology
India
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Department of Electronics and Communication Engineering
National Institute of Technology
India
Homepage1. Yuan, N., C. Ruan, and W. Lin, "Analytical analyses of V, elliptic, and circular shaped microshield transmission lines," IEEE Trans. Microwave Theory Tech., Vol. 42, 855-859, May 1994.
doi:10.1109/22.293535 Google Scholar
2. Simons, R. N., "Coplanar Waveguide Circuits, Components and Systems," John Wiley & Sons, Inc., 2001. Google Scholar
3. Dib, N. I., W. P. Harokopus Jr., P. B. Katechi, C. C. Ling, and G. M. Rebeiz, "Study of a novel planar transmission line," IEEE MTT-S Digest, 623-626, 1991. Google Scholar
4. Lee, J.-W., I.-P. Hong, T.-H. Yoo, and H.-K. Park, "Quasi-static analysis of conductor backed coupled CPW," IEEE Electronics Letters, Vol. 34, No. 19, 1861-1862, Sep. 1998.
doi:10.1049/el:19981268 Google Scholar
5. Gevorgian, S., L. J. Peter Linner, and E. L. Kollberg, "CAD models for shielded multilayered CPW," IEEE Trans. Microwave Theory Tech., Vol. 43, 772-779, Apr. 1995.
doi:10.1109/22.375223 Google Scholar
6. Du, Z. and C. Ruan, "Analytical analysis of circular-shaped microshield and conductor-backed coplanar wave guide," International Journal of Infrared and Millimeter Waves, Vol. 18, No. 1, 165-171, 1997.
doi:10.1007/BF02677903 Google Scholar
7. Yildiz, C. and M. Turkmen, "Quasi-static models based on artificial neural networks for calculating the characteristic parameters of multilayer cylindrical coplanar waveguide and strip line," Progress In Electromagnetics Research B, Vol. 3, 1-22, 2008.
doi:10.2528/PIERB07112806 Google Scholar
8. Kaya, S., M. Turkmen, K. Guney, and C. Yildiz, "Neural models for the elliptic- and circular-shaped microshield lines," Progress In Electromagnetics Research B, Vol. 6, 169-181, 2008.
doi:10.2528/PIERB08031216 Google Scholar
9. Zhang, Q. J. and K. C. Gupta, "Neural Networks for RF and Microwave Design," Artech House, 2000. Google Scholar
10. Haykin, S., Neural Networks: A Comprehensive Foundation, Macmillan College Publishing Comp., 1994.
11. Yildiz, C., K. Guney, M. Turkmen, and S. Kaya, "Neural models for coplanar strip line synthesis," Progress In Electromagnetics Research, Vol. 69, 127-144, 2007.
doi:10.2528/PIER06120802 Google Scholar
12. Fun, M.-H. and T. Martin Hagan, "Levenberg-marquardt training for modular networks," Proceedings of the 1997 International Joint Conference on Neural Networks, 468-473, 1996. Google Scholar
13. Levenberg, K., "A method for the solution of certain nonlinear problems in least squares," Quarterly of Applied Mathematics, Vol. 11, 431-441, 1963. Google Scholar
14. Mackay, D. J. C., "Bayesian interpolation," Neural Computation, Vol. 3, No. 4, 415-447, 1992.
doi:10.1162/neco.1992.4.3.415 Google Scholar
15. Foresee, F. D. and M. T. Hagan, "Gauss-Newton approximation to Bayesian regularization," Proceedings of the 1997 International Joint Conference on Neural Networks, 1930-1935, 1997. Google Scholar
16. Gill, P. E., "Practical Optimization," Academic Press, 1981. Google Scholar
17. Fletcher, R. and C. M. Reeves, "Function minimization by conjugate gradients," Computer Journal, Vol. 7, 149-154, 1964.
doi:10.1093/comjnl/7.2.149 Google Scholar
18. Moller, M. F., "A scaled conjugate gradient algorithm for fast supervised learning," Neural Networks, Vol. 6, 525-533, 1993.
doi:10.1016/S0893-6080(05)80056-5 Google Scholar
19. Dennis, E. and R. Schnabel, Numerical Methods for Unconstrained Optimization and Nonlinear Equations, Prentice Hall, 1983.
