Modeling of double ridge waveguide using ANN

doi:10.1007/s11460-012-0200-4

Front Elect Electr Eng

2012, Vol. 7

Issue (3) : 299-307 https://doi.org/10.1007/s11460-012-0200-4

RESEARCH ARTICLE

Modeling of double ridge waveguide using ANN

J. LAKSHMI NARAYANA(

), K. SRI RAMA KRISHNA, L. PRATAP REDDY, G. V. SBRAHMANYAM

Department of Electronics & Communication Engineering, St. Ann’s College of Engineering and Technology, Chirala, A.P., India

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Abstract

The ridge waveguide is useful in various microwave applications because it can be operated at a lower frequency and has lower impedance and a wider mode separation than a simple rectangular waveguide. An accurate model is essential for the analysis and design of ridge waveguide that can be obtained using electromagnetic simulations. However, the electromagnetic simulation is expensive for its high computational cost. Therefore, artificial neural networks (ANNs) become very useful especially when several model evaluations are required during design and optimization. Recently, ANNs have been used for solving a wide variety of radio frequency (RF) and microwave computer-aided design (CAD) problems. Analysis and design of a double ridge waveguide has been presented in this paper using ANN forward and inverse models. For the analysis, a simple ANN forward model is used where the inputs are geometrical parameters and the outputs are electrical parameters. For the design of RF and microwave components, an inverse model is used where the inputs are electrical parameters and the outputs are geometrical parameters. This paper also presents a comparison of the direct inverse model and the proposed inverse model.

Keywords ridge waveguide radio frequency (RF) computer-aided design (CAD) artificial neural network (ANN) forward and inverse models

Corresponding Author(s): LAKSHMI NARAYANA J.,Email:jln_9976@yahoo.com

Issue Date: 05 September 2012

Cite this article:

J. LAKSHMI NARAYANA,K. SRI RAMA KRISHNA,L. PRATAP REDDY, et al. Modeling of double ridge waveguide using ANN[J]. Front Elect Electr Eng, 2012, 7(3): 299-307.

URL:

https://academic.hep.com.cn/fee/EN/10.1007/s11460-012-0200-4
https://academic.hep.com.cn/fee/EN/Y2012/V7/I3/299

Fig.1 Ridge waveguide. (a) Single ridge waveguide; (b) double ridge waveguide; (c) equivalent circuit

Fig.2 Neural model for calculating normalized cutoff wavelength (/) of a double ridge waveguide (forward model)

Fig.3 Flow chart showing neural network training and neural model testing

Tab.1 Training and test results for normalized cutoff wavelength (/) of a double ridge waveguide of forward model
(a) Training results

Tab.2 (b) Test results

Fig.4 Comparison of normalized center section width (/) vs. normalized cutoff wavelength (/) obtained using the simulated results with that of the forward model of a double ridge waveguide

Fig.5 Neural model for calculating normalized center section width (/) of a double ridge waveguide (direct inverse model)

Tab.3 Training and test results for normalized center section width (/) of a double ridge waveguide of neural direct inverse model
(a) Training results

Tab.4 (b) Test results

Fig.6 Comparison of normalized cutoff wavelength (/) vs. normalized center section width (/) obtained using the simulated results with that of the direct inverse model of a double ridge waveguide

Fig.7 Diagram of inverse model

Fig.8 Comparison of normalized cutoff wavelength (/) vs. normalized center section width (/) obtained using the simulated results with that of the neural model (direct inverse model, proposed inverse model) of a double ridge waveguide

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