Title :
Fast extraction of L & C parameters of MEMS Transmission Line using Neural Network
Author :
Patnaik, Prabhat K. ; Panda, Dhruba C.
Author_Institution :
Dept. of E.C.E, Centurion Univ. of Technol. & Manage., Paralakhemundi, India
Abstract :
Presently “equivalent Inductance L” and “equivalent Capacitance C” values of Distributed MEMS Transmission Line (DMTL) are found using EM optimization technique. In this paper, we propose an efficient approach using Neural Network (NN) for extraction of L and C values of DMTL. This method takes less computational resource. The LC values extracted from the neural network model are compared with EM simulation results.
Keywords :
electronic engineering computing; micromechanical devices; neural nets; transmission lines; EM optimization technique; EM simulation; LC value extraction; NN; computational resource; distributed DMTL; distributed MEMS Transmission Line; equivalent Inductance extraction; equivalent capacitance extraction; mems transmission line; neural network model; Artificial neural networks; Computational modeling; Mathematical model; Micromechanical devices; Power transmission lines; Solid modeling; capacitance; inductance; mems; neural network; transmission line;
Conference_Titel :
Applied Electromagnetics Conference (AEMC), 2013 IEEE
Conference_Location :
Bhubaneswar
Print_ISBN :
978-1-4799-3266-5
DOI :
10.1109/AEMC.2013.7045082
