Title :
A method of life signal identification based on BP neural network
Author_Institution :
Preps Dept. of Eng. Coll. of the Chinese, People´´s Armed Police Force, Xian, China
Abstract :
Ultra wide band (UWB) life detector can penetrate walls and ruins to detect whether there is a sign of life on the rear. This device will play an important role in anti-terrorism and disaster relief. But because the life signal is low frequency, quasi-periodic, non-stationary and low signal to noise ratio (SNR) and so on, such features restrict the accuracy of identifying life signals. According to the characteristics of life signals, back propagation (BP) neural network is chosen as the life signal recognition method, and the proper network structure is designed with appropriate network parameters selected. Simulation results show that, using BP neural network method can greatly improve the life signal identification accuracy; it is proved to be an effective method in the practical project.
Keywords :
backpropagation; disasters; signal processing; BP neural network; SNR; UWB life detector; anti-terrorism; disaster relief; life signal identification; life signal recognition method; low frequency; low signal to noise ratio; nonstationary; quasiperiodic; ultra wide band; Accuracy; Biological neural networks; Detectors; Frequency domain analysis; Signal to noise ratio; Training; BP neural network; life detector; life signal identification; simulation in MATLAB;
Conference_Titel :
Image and Signal Processing (CISP), 2011 4th International Congress on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-9304-3
DOI :
10.1109/CISP.2011.6099970