Title :
A frequency reconfigurable antenna design using neural networks
Author :
Patnaik, Amalendu ; Anagnostou, Dimitrios ; Christodoulou, Christos G. ; Lyke, James C.
Author_Institution :
Dept. Electron. & Commun. Eng., Nat. Inst. of Sci. & Tech, Orissa, India
Abstract :
In this work, design aspects of a frequency reconfigurable antenna are handled using neural networks. The job of the neural network is to determine the switches that are to be made ON for the structure to resonate at specific bands. This task is handled as a classification type of problem and is accomplished by a self-organizing map neural network (SOM NN).
Keywords :
multifrequency antennas; pattern classification; self-organising feature maps; SOM NN; classification problem; frequency reconfigurable antenna; self-organizing map neural network; switches; Bandwidth; Design engineering; Frequency response; Laboratories; Microswitches; Multifrequency antennas; Neural networks; Receiving antennas; Switches; Transmitting antennas;
Conference_Titel :
Antennas and Propagation Society International Symposium, 2005 IEEE
Print_ISBN :
0-7803-8883-6
DOI :
10.1109/APS.2005.1551830
