Title :
Microwave Devices and Antennas Modelling by Support Vector Regression Machines
Author :
Angiulli, G. ; Cacciola, M. ; Versaci, M.
Author_Institution :
DIMET, Mediterranea Univ., Calabria
Abstract :
Artificial neural networks have been employed as a fast tool for microwave device modelling. Support vector machines developed by Vapnik are gaining popularity due to many attractive features capable to overcome the limitations connected to ANNs. In this work, we discuss the use of support vector regression machines for microwave devices and antenna modelling
Keywords :
electrical engineering computing; microwave antennas; neural nets; support vector machines; antennas; artificial neural networks; microwave devices; support vector regression machines; Artificial neural networks; Biomedical engineering; Biomedical signal processing; Computational electromagnetics; Lab-on-a-chip; Microwave antennas; Microwave devices; Performance analysis; Support vector machines; Wireless communication;
Conference_Titel :
Electromagnetic Field Computation, 2006 12th Biennial IEEE Conference on
Conference_Location :
Miami, FL
Print_ISBN :
1-4244-0320-0
DOI :
10.1109/CEFC-06.2006.1633092
