Title :
Antenna recognition based on BP neural network
Author :
Chunyan Zhao ; Dan Shi ; Yougang Gao
Author_Institution :
Sch. of Electron. Eng., Beijing Univ. of Posts & Telecommun., Beijing, China
Abstract :
This paper studies several commonly used algorithms in the BP neural network. Training the BP neural network under these different algorithms can see the various performance of their networks. The study of both classical BP algorithm and LM algorithm will find the improvements of LM algorithm. In addition, practical applications show the following two things. For one hand, different BP algorithm impacts the speed of the network. For the other, the number of hidden layer neurons is also a sensitive factor to the performance of BP neural network. On the basis of the BP neural network, we want to build a suitable antenna model and use it in the identification of the antennas, it will have great practical significance.
Keywords :
antennas; backpropagation; neural nets; radiocommunication; BP neural network; LM algorithm; antenna recognition; Algorithm design and analysis; Biological neural networks; Microwave antennas; Neurons; Standards; Training; BP neural network; LM algorithm; classic BP algorithm; hidden layer nodes;
Conference_Titel :
Environmental Electromagnetics (CEEM), 2012 6th Asia-Pacific Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4673-0030-8
DOI :
10.1109/CEEM.2012.6410642