@article{(Open Science Index):https://publications.waset.org/pdf/5376,
	  title     = {Artificial Neural Network based Parameter Estimation and Design Optimization of Loop Antenna},
	  author    = {Kumaresh Sarmah and  Kandarpa Kumar Sarma},
	  country	= {},
	  institution	= {},
	  abstract     = {Artificial Neural Network (ANN)s are best suited for
prediction and optimization problems. Trained ANNs have found
wide spread acceptance in several antenna design systems. Four
parameters namely antenna radiation resistance, loss resistance, efficiency,
and inductance can be used to design an antenna layout though
there are several other parameters available. An ANN can be trained
to provide the best and worst case precisions of an antenna design
problem defined by these four parameters. This work describes the
use of an ANN to generate the four mentioned parameters for a loop
antenna for the specified frequency range. It also provides insights
to the prediction of best and worst-case design problems observed
in applications and thereby formulate a model for physical layout
design of a loop antenna.},
	    journal   = {International Journal of Electronics and Communication Engineering},
	  volume    = {4},
	  number    = {8},
	  year      = {2010},
	  pages     = {1180 - 1186},
	  ee        = {https://publications.waset.org/pdf/5376},
	  url   	= {https://publications.waset.org/vol/44},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 44, 2010},
	}