Analysis of conductor-backed coplanar waveguides using adaptive-network-based fuzzy inference system models

✍ Scribed by Celal Yildiz; Kerim Guney; Mustafa Turkmen; Sabri Kaya

• Publisher: John Wiley and Sons
• Year: 2009
• Tongue: English
• Weight: 193 KB
• Volume: 51
• Category: Article
• ISSN: 0895-2477
• DOI: 10.1002/mop.24059

✦ Synopsis

Abstract

A method based on adaptive‐network‐based fuzzy inference system (ANFIS) is presented for the quasi‐static analysis of conductor‐backed coplanar waveguides. The ANFIS is a class of adaptive networks which are functionally equivalent to fuzzy inference systems. Four optimization algorithms, hybrid learning, genetic, simulated annealing, and least‐squares, are used to determine optimally the design parameters of the ANFIS. The results of ANFIS are compared with the results of experimental works, quasi‐static and full‐wave spectral domain approaches, conformal mapping technique, and a commercial electromagnetic simulator IE3D. The results of ANFIS models are in very good agreement with the results of other methods and experimental works. When the performances of ANFIS models are compared with each other, the best result is obtained from the ANFIS model trained by the hybrid learning algorithm. © 2008 Wiley Periodicals, Inc. Microwave Opt Technol Lett 51: 439–445, 2009; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.24059