Title :
Neuro-modeling of simulated miniature rectangular microstrip antenna by using feed forward and feed back propagation
Author :
Mishra, Anadi ; Janvale, G. ; Kasar, S. ; Pawar, Bhausaheb V. ; Patil, A.J.
Author_Institution :
Dept. of Electron. Eng., North Maharashtra Univ., Jalgaon, India
Abstract :
Neural-network computational modules have been recently gained recognition as an unconventional and useful tool for RF and microwave modeling and design. Neural networks can be trained to learn the behavior of passive/active components/circuits. This work presents Artificial Neural Network for design of IE3D simulated miniature microstrip antenna. In the presented work, artificial neural network is used for accurate determination of the different parameters like resonant frequency, bandwidth, return loss and voltage standing wave ratio of square and rectangular microstrip patch antenna. The developed neural network model which uses the data of simulated hundred antennas, is based on feed-forward and feedback propagation. The comparative analysis of developed models are presented which gives higher accuracy reported else where.
Keywords :
microstrip antennas; IE3D simulated miniature microstrip antenna; artificial neural network computational modules; feedback propagation; feedforward; microwave modeling; neural network model; neuro modeling; passive/active components/circuits; rectangular microstrip patch antenna; resonant frequency; simulated miniature rectangular microstrip antenna; voltage standing wave ratio; Artificial neural networks; Computational modeling; Microstrip antennas; Microwave circuits; Solid modeling; Training; ANN (Artificial Neural Network); CG (Conjugate Gradient); HQN (Huber Quasi Newton); RBF (Radial basis function); RMSA (Rectangular microstrip antenna);
Conference_Titel :
Applied Electromagnetics Conference (AEMC), 2011 IEEE
Conference_Location :
Kolkata
Print_ISBN :
978-1-4577-1098-8
DOI :
10.1109/AEMC.2011.6256830