Design of Microwave Filter Using Segmentation, Coupling Matrix and Neural Network

Chahrazad Erredir¹, Mohamed Lhadi Riabi²

Laboratory of Electromagnetism and Telecommunications, Department of Electronic University Constantine1.

Abstract

In this paper, neural network modeling techniques are applied for modeling and design of microwave filter, where neural networks and filter coupling matrix are combined in an innovative way to deliver speed and accuracy of the overall filter design. Filter structure is decomposed into sub-structures representing each coupling mechanism, where the decomposition is used to simplify the overall high-dimensional neural- network modeling problem into a set of low-dimensional-network problem. Generalized scattering matrices (GSM) of the modules are calculated using mode-matching method. Equivalent circuit parameters, such as coupling value and insertion phase lengths are then extracted from EM data. Neural network models are developed for each individual module, and arethen combined to form a complete model. Good agreement is obtained between neural models and EM based data, where the proposed technique is very useful for neural-based microwave optimization and synthesis. Application of the method to a three cavity waveguide filter is presented.

Keywords

• Segmentation method, coupling matrix, equivalent circuit, microwave filter, neural networks

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Cite this Article as Follows

Chahrazad Erredir, Mohamed Lhadi Riabi. Design of Microwave Filter Using Segmentation, Coupling Matrix and Neural Network. International Conference on Nanoelectronics, Communications and Renewable Energy 2013. Vol. 1. Chennai: Association of Scientists, Developers and Faculties, 2013. 180-183. Print.