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Very simple computer-aided-design models are introduced to determine the characteristic parameters such as effective permittivities and characteristic impedances of unshielded suspended and inverted microstrip lines. Computeraided-design models are determined with the use of the genetic programming. The results of computer-aided-design models are compared with the results of quasi-static analysis, experimental works available in the literature and a commercial electromagnetic simulator. The comparison results clearly show that computer-aided-design models proposed in this work are in very good agreement with the simulation, theoretical and experimental results for the suspended and inverted microstrip lines. The design parameter ranges in this work are 2 ≤ εr2 ≤ 20, 0.5 ≤ w/b ≤ 10, 0.1 ≤ a/b ≤ 1.5, and the respective characteristic impedances of unshielded suspended and inverted microstrip lines are 28Ω ≤ Z0 ≤ 185, and 24 Ω ≤ Z0 ≤ 159 Ω, respectively. It is observed that the accuracies of computer-aided-design models proposed in this paper are good enough for the most practical cases. [ABSTRACT FROM AUTHOR]

In this paper, numerical analysis of the narrow microstrip transmission-line on two and three layer-substrate material at 0.5-1.0 THz frequency of the electromagnetic spectrum is presented. Various analytical results are compared with simulations which have been performed by commercially available simulators: (a) CST Microwave Studio based on the finite integral technique and (b) Ansoft HFSS based on the finite element technique. The proposed narrow microstrip transmission line with improved performance is useful as interconnect for multilayer planar components designed in the terahertz frequency regime of the electromagnetic spectrum. The analysis of the proposed structure has been validated with various reported literature. [ABSTRACT FROM AUTHOR]

In this work, computer-aided design models based on adaptive-network-based fuzzy inference system (ANFIS) for the quasistatic analysis of three different coplanar strip line structures are presented. These strip line structures are conventional coplanar strip lines, asymmetrical coplanar strip lines with infinitely wide strip, and asymmetrical coplanar strip lines with infinitely thick dielectric substrate. The design parameters of the proposed ANFIS models are optimally determined by using four different optimization algorithms, hybrid learning, simulated annealing, least-squares, and genetic algorithm. When the performances of ANFIS models are compared with each other, the best results for training and test are obtained from the models trained with hybrid learning algorithm. There is a good agreement among the results of ANFIS models, quasistatic analysis, a full-wave electromagnetic simulator IE3D, and experimental works realized in this study. © 2010 Wiley Periodicals, Inc. Microwave Opt Technol Lett 52: 1990–1996, 2010; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.25372 [ABSTRACT FROM AUTHOR]

A method based on adaptive-network-based fuzzy inference system (ANFIS) is presented for the quasi-static analysis of conductor-backed coplanar waveguides. The ANFIS is a class of adaptive networks which are functionally equivalent to fuzzy inference systems. Four optimization algorithms, hybrid learning, genetic, simulated annealing, and least-squares, are used to determine optimally the design parameters of the ANFIS. The results of ANFIS are compared with the results of experimental works, quasi-static and full-wave spectral domain approaches, conformal mapping technique, and a commercial electromagnetic simulator IE3D. The results of ANFIS models are in very good agreement with the results of other methods and experimental works. When the performances of ANFIS models are compared with each other, the best result is obtained from the ANFIS model trained by the hybrid learning algorithm. © 2008 Wiley Periodicals, Inc. Microwave Opt Technol Lett 51: 439–445, 2009; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.24059 [ABSTRACT FROM AUTHOR]

This article presents a new method based on adaptive neuro-fuzzy inference system (ANFIS) to calculate the effective permittivities and characteristic impedances of microstrip lines. The ANFIS is a fuzzy inference system (FIS) implemented in the framework of an adaptive fuzzy neural network. It has the advantages of expert knowledge of FISs and learning capability of artificial neural networks. A hybrid learning algorithm, which combines the least square method and the back propagation algorithm, is used to identify the parameters of ANFIS. The results of ANFIS are compared with the results of the experimental works, quasi-static methods, and a commercial electromagnetic simulator IE3D. There is very good agreement among the results of ANFIS models and quasi-static methods, IE3D, and experimental works. © 2008 Wiley Periodicals, Inc. Microwave Opt Technol Lett 50: 1191–1196, 2008; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.23322 [ABSTRACT FROM AUTHOR]

Abstract: Neural models based on multilayered perceptrons (MLPs) for computing the effective permittivities and the characteristic impedances of both the conventional coplanar waveguides (CCPWs) and the supported coplanar waveguides (SCPWs) are presented. Six learning algorithms, Levenberg–Marquardt (LM), Bayesian regularization (BR), quasi-Newton (QN), scaled conjugate gradient (SCG), conjugate gradient of Fletcher–Powell (CGF), and resilient propagation (RP), are used to train the MLPs. The results of neural models presented in this paper are compared with the results of the experimental works, the conformal mapping technique (CMT), the spectral domain approach (SDA), and three commercial electromagnetic simulators such as IE3D, CAPIND2D, and MMICTL. The neural results are in very good agreement with the theoretical and experimental results. When the performances of neural models are compared with each other, the best result is obtained from the MLPs trained by the LM algorithm. [Copyright &y& Elsevier]

Neural models based on the artificial neural networks (ANNs) for computing the effective permittivities and characteristic impedances of V-shaped conductor-backed coplanar waveguides are presented. The proposed neural models can also be used for calculating the characteristic parameters of conductor-backed coplanar waveguides. Six learning algorithms, Levenberg–Marquardt, bayesian regularization, quasi–Newton, scaled conjugate gradient, conjugate gradient of Fletcher-Reeves, and resilient propagation, are used to train the ANNs. The neural results are in very good agreement with the results available in the literature. When the performances of neural models are compared with each other, the best result is obtained from the ANNs trained by the LM algorithm. © 2007 Wiley Periodicals, Inc. Microwave Opt Technol Lett 49: 1294–1299, 2007; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.22473 [ABSTRACT FROM AUTHOR]

This article presents a new approach based on multilayered perceptron neural networks (MLPNNs) to calculate the odd-and even-mode characteristic impedances and effective permittivities of the broadside-coupled V-shaped microshield coplanar waveguides (BC-VSMCPWs). Six learning algorithms, bayesian regulation (BR), Levenberg-Marquardt (LM), quasi-Newton (QN), scaled conjugate gradient (SCG), resilient propagation (RP), and conjugate gradient of Fletcher-Powell (CGF), are used to train the MLPNNs. The neural results are in very good agreement with the results reported elsewhere. When the performances of neural models are compared with each other, the best and worst results are obtained from the MLPNNs trained by the BR and CGF algorithms, respectively. [ABSTRACT FROM AUTHOR]

This article presents a new approach based on artificial neural networks (ANNs) to determine the characteristic parameters of symmetric and asymmetric coplanar waveguides with a finite dielectric thickness. ANNs are trained with the use of five training algorithms. The results obtained from neural models are in very good agreement with the theoritical and experimental results available in the literature. © 2003 Wiley Periodicals, Inc. Int J RF and Microwave CAE 13: 438–446, 2003. [ABSTRACT FROM AUTHOR]

The dispersion characteristics of the dominant mode in V-shaped microstrip lines are investigated using the finite-difference time-domain (FDTD) method. Such V-shaped microstrip lines are assumed to be fabricated on a single-layer isotropic substrate. The hybrid effects of the inclined angle of the metal wall and the permittivity of the filling material on the effective permittivity and characteristic impedance are examined and compared. © 2003 Wiley Periodicals, Inc. Microwave Opt Technol Lett 38: 320–323, 2003; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.11049 [ABSTRACT FROM AUTHOR]