Design and optimization of CPW circuits using EM-ANN models for CPW components

Watson, Paul; Gupta, K.C.

doi:10.1109/22.643868

Cited by 199 publications

(90 citation statements)

References 32 publications

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“…One of the fields that experts recently have been working on is toward the development of accurate and efficient methods for EM simulation of CPW discontinuities, but the challenge of using these tools for iterative CAD and circuit optimization [37] is the timeconsuming nature of EM simulation. To overcome this problem, EM-ANN models have been suggested [38]. The models include CPW transmission line, short-and open-circuit stubs, stepin width discontinuities, and T-junctions.…”

Section: Em-ann Models For Cpw Componentsmentioning

confidence: 99%

Modeling and Simulation Techniques for Microwave Components

Mohammadi¹,

Sadrossadat²

2017

Microwave Systems and Applications

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This chapter discusses about methods used in simulation and modeling of radio frequency (RF)/microwave circuits and components. The main topic that is discussed here is about one of the most powerful methods, that is, artificial neural networks. In this chapter, different types of neural network such as dynamic and recurrent neural networks will be discussed. Other techniques that are popular in the area of microwave components simulation and modeling are numerical techniques such as vector fitting, Krylov method, and Pade approximation. At the end of the chapter, vector fitting as an example of numerical methods will be discussed.Keywords: artificial neural networks, circuit simulation and modeling, transient analysis, function approximation, RF/microwave circuits IntroductionIn recent years, ascending development of wireless communication products and huge trend for commercial market in this ground caused significant improvement in modeling and simulation approaches of radio frequency (RF) and microwave circuits. Such high-frequency circuits are leading to the development of a large variety of microwave models for passive and active devices and circuit components [1]. Modeling and computer-aided design (CAD) methods have an essential role in microwave designs and simulations [2]. The older approaches were mainly based on slow trial-and-error processes and an emphasis on performance at any price, but today seems to be a new era in high-frequency circuit design and modeling, since development in this ground has enabled microwave engineers to design larger, more efficient, and more complicated circuits than before [1,3]. This complexity requires new materials and technologies that require not only new models but also new © 2017 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.algorithms in computer-aided design [4] for RF/microwave circuits, antennas, and systems to keep up with the advancement of technology with emphasis on time-to-market and low-cost approaches [1,3]. In addition to accurate parametric-modeling techniques to describe the behavior of the microwave device, a reliable description that explains the changes of its behavior against geometrical or physical parameters is also needed [5].Also, since circuit models at high frequencies often lack fidelity, detailed electromagnetic (EM) simulation techniques are needed to improve design accuracy. Although EM simulation techniques are heavily used yet, they are computationally expensive, so there is a demand for design methodologies to be not only accurate but also fast. Another concerning problem today is optimization. To meet this purpose, computer-based algorithms that work with iterative circuit evaluation are needed; this process also needs a highly repetitive computational process. Another concerning issue a...

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Section: Em-ann Models For Cpw Componentsmentioning

confidence: 99%

Modeling and Simulation Techniques for Microwave Components

Mohammadi¹,

Sadrossadat²

2017

Microwave Systems and Applications

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“…NN techniques are in use for a wide variety of microwave applications such as embedded passives [5], transmission line components [6][7][8], vias [9], bends [10], coplanar waveguide (CPW) components [11], spiral inductors [12], FETs [13], amplifiers [14,15], etc. NNs are used in impedance matching [16,17], inverse modeling [18], measurements [19], and synthesis [20].…”

Section: Neural Network Developmentmentioning

confidence: 99%

Levenberg-Marquardt and Conjugate Gradient Neuro-Modeling of Simulated Miniature Rectangular Microstrip Antenna

Mishra¹,

Janvale²,

Kasar³

et al. 2012

Advanced Computational Techniques in Electromagnetics

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Neural-network computational modules have recently gained recognition as an unconventional and useful tool for RF and microwave modeling and design. Neural networks can be trained to learn the behaviour of passive/active components/circuits. This work presents artificial neural network (ANN) for design of IE3D simulated miniature microstrip antenna. In the presented work, the artificial neural network is used for accurate determination of different parameters like resonant frequency, bandwidth, return loss, and voltage standing wave ratio (VSWR) of square and rectangular microstrip patch antenna. The developed neural network model which uses the data of simulated hundred antennas is based on Levenberg-Marquardt (LM) and conjugate gradient (CG) feed-back propagation. The developed ANN models for rectangular microstrip antennas (RMSAs) are in very good agreement with the experimental results available in the literature. The comparative analysis of developed models is presented which gives higher accuracy than that reported elsewhere.

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“…The application of ANN on the field of microstrip patch antenna is very recent. A number of papers [28][29][30][31][32][33][34][35][36][37][38][39][40][41][42][43][44] are present in the literature that signifies the importance of ANN in the field of microstrip patch antenna.…”

Section: Introductionmentioning

confidence: 99%

Design and Analysis of Microstrip Line Feed Toppled T Shaped Microstrip Patch Antenna using Radial Basis Function Neural Network

Aneesh¹,

Kumar²,

Singh³

et al. 2015

Journal of Electrical Engineering and Technology

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-This paper deals with the design of a microstrip line feed toppled T shaped microstrip patch antenna that gives dualband characteristics at 4 GHz and 6.73 GHz respectively. The simulation of proposed antenna geometry has been performed using method of moment based IE3D simulation software. A radial basis function neural network (RBFNN) is used for the estimation of bandwidth for dualband at 4 GHz and 6.73 GHz respectively. In RBFNN model, antenna parameters such as dielectric constant, height of substrate, and width are used as input and bandwidth of first and second band is considered as output of the network. To validate the RBFNN output, an antenna has been physically fabricated on glass epoxy substrate. The fabricated antenna can be utilized in S and C bands applications. RBFNN results are found in close agreement with simulated and experimental results.

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Design and optimization of CPW circuits using EM-ANN models for CPW components

Cited by 199 publications

References 32 publications

Modeling and Simulation Techniques for Microwave Components

Modeling and Simulation Techniques for Microwave Components

Levenberg-Marquardt and Conjugate Gradient Neuro-Modeling of Simulated Miniature Rectangular Microstrip Antenna

Design and Analysis of Microstrip Line Feed Toppled T Shaped Microstrip Patch Antenna using Radial Basis Function Neural Network

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