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Cylindrical post-based waveguide filters are a relevant component of antenna feeding networks. Their synthesis performed via automatic optimization based on full-wave analyses can be very time consuming. In this article a novel fast-design approach based on Levy's and Moore's algorithms and an artificial neural network (ANN) architecture is presented. © 2006 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2006. [ABSTRACT FROM AUTHOR]

This paper deals with many different neural network architectures that have been introduced to simulate the electromagnetic behavior of complex microwave devices and antennas. Many issues linked to the peculiarities of such devices are addressed. Furthermore, the inverse problem of designing a microwave device, once the required characteristics are given, is also developed by using a neural network approach. © 2002 John Wiley & Sons, Inc. Int J RF and Microwave CAE 12: 90–97, 2002. [ABSTRACT FROM AUTHOR]

In many filtering applications, direct-coupled cavity filters are often used for their symmetry and handling easiness. In this paper, a method is described for the design of these filtering devices by using an artificial neural network (ANN). Starting from design requirements, the procedure discussed herein directly determines the geometric dimensions of the filtering device with good accuracy and very short processing time. ©1999 John Wiley & Sons, Inc. Int J RF and Microwave CAE 9: 287–296, 1999. [ABSTRACT FROM AUTHOR]