Title :
Study of BP neural network´s weights based on acoustic resonance spectroscopy
Author :
Du Huanchao ; Fang Jianqing ; Li Hongjun ; Ma Chao ; Cui Kaihua
Abstract :
This paper carries out a preliminary study of BP neural network´s weights, and uses the weights to analyze the acoustic resonance spectroscopy (ARS) of the structure´s state. The results indicate that the weights show promise in telling the sensitive frequencies when the structure´s state changed.
Keywords :
acoustic resonance; backpropagation; neural nets; spectroscopy; ARS; BP neural network; acoustic resonance spectroscopy; sensitive frequencies; Acoustics; Neurons; Programming; Resonant frequency; Spectroscopy; Time frequency analysis; Training; BP neural network; acoustic resonance spectroscopy; state identification; weight;
Conference_Titel :
Information Technology and Artificial Intelligence Conference (ITAIC), 2011 6th IEEE Joint International
Conference_Location :
Chongqing
Print_ISBN :
978-1-4244-8622-9
DOI :
10.1109/ITAIC.2011.6030277
