Title :
Wavelength calibration based on back propagation neural network
Author :
Liang Zhang ; Yinzhen Dai ; Chun Lin ; Ruiqi Lyu ; Lei Wang ; Tianlin Hu
Author_Institution :
Sch. of Phys. & Mech. & Electr. Eng., Xiamen Univ., Xiamen, China
Abstract :
A method based on Back Propagation Neural Network (BPNN) for wavelength calibration of Spectrometer is proposed in this paper. An appropriate neural network is constructed to map pixel location in CCD to the wavelength with any given grating position. In this method, input vector of the network involves the center wavelength of the spectrometer and the pixel location, output vector of the network is the spectral wavelength that has been corrected. And standard spectral lines from a Neon light are used for training of the neural network Compared with traditional method based on correction formula, this method reduces the mean error by 55.6% with the center wavelength range from 608nm to 668nm.
Keywords :
backpropagation; calibration; charge-coupled devices; computerised instrumentation; neural nets; spectrometers; BPNN; CCD; backpropagation neural network; grating position; map pixel location; neon light; standard spectral line; training; wavelength 608 nm to 668 nm; wavelength calibration; Calibration; Charge coupled devices; Equations; Gratings; Neural networks; Standards; Training; grating spectrometer; neural network; wavelength calibration;
Conference_Titel :
Anti-counterfeiting, Security, and Identification (ASID), 2014 International Conference on
Print_ISBN :
978-1-4799-7117-6
DOI :
10.1109/ICASID.2014.7064972
