Predicting the Frequency Characteristics of Hybrid Meander Systems Using a Feed-Forward Backpropagation Network

Darius Plonis,Robertas Damaševičius,Rytis Maskeliūnas,Vaiva Šlegerytė,Andrius Katkevičius,Audrius Krukonis

doi:10.3390/electronics8010085

Darius Plonis, Robertas Damaševičius + Show 4 more

Open Access

https://doi.org/10.3390/electronics8010085

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Abstract

The process of designing microwave devices is difficult and time-consuming because the analytical and numerical methods used in the design process are complex. Therefore, it is necessary to search for new methods that will allow for an acceleration of synthesis and analytic procedures. This is especially important in cases where the procedures of synthesis and analysis have to be repeated many times, until the correct device configuration is found. Artificial neural networks are one of the possible alternatives for the acceleration of the design process. In this paper we present a procedure for analyzing a hybrid meander system (HMS) using the feed-forward backpropagation network (FFBN). We compared the prediction results of the transmission factor and the reflection factor , obtained using the FFBN, with results obtained using traditional analytical and numerical methods, as well as with experimental results. The comparisons show that prediction results significantly depend on the FFBN structure. In terms of the lowest difference between the characteristics calculated using the method of moments (MoM) and characteristics predicted using the FFBN, the best prediction was achieved using the FFBN with three hidden layers, which included 18 neurons in the first hidden layer, 14 neurons in the second hidden layer, and 2 neurons in the third hidden layer. Differences between the predicted and calculated results did not exceed 7% for the parameter and 5% for the parameter. The prediction of parameters using the FFBN allowed the analysis procedure to be sped up from hours to minutes. The experimental results correlated with the predicted characteristics.

Highlights

IntroductionThe manufacture of microwave devices usually consists of several stages: (1) synthesis of physical and geometrical parameters using analytical and numerical iterative methods [1,2,3,4],
The manufacture of microwave devices usually consists of several stages: (1) synthesis of physical and geometrical parameters using analytical and numerical iterative methods [1,2,3,4],(2) analysis of synthesized models using analytical and numerical iterative methods [5,6,7,8,9], and (3) experimental verification [10,11,12,13,14]
The most time-consuming stage is the repetition of experimental verification, as this requires the manufacturing of another experimental prototype of the device

Summary

Introduction

The manufacture of microwave devices usually consists of several stages: (1) synthesis of physical and geometrical parameters using analytical and numerical iterative methods [1,2,3,4],. (2) analysis of synthesized models using analytical and numerical iterative methods [5,6,7,8,9], and (3) experimental verification [10,11,12,13,14] This procedure is usually time consuming, especially when the approximate parameters are not known and many synthesis iterations are required [15,16]. Calculation time using the analytical methods is quite short, but the preparation procedure and the development of a specific mathematical model for every particular design of a microwave device is a long process and requires a great deal of domain knowledge [6]

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