Terahertz Spectrum Recognition of Pathogens Based on PCA-Siamese Neural Network

Abstract

In the terahertz timedomain spectroscopy technique , 16 c ommon pathogens were experimentally studied and their characteri stics absorption spectra in the frequency range of 0.1 to 2.2THz wer e obtained . The terahertz absorption spectra of 16 common pathog ens were trained and identified by Siamese neural network method . First , the terahertz absorption spectra of the 16 pathogens were re duced by PCA to construct training data . Then , the constructed Si amese neural network model was trained by back propagation . Fin ally , the pathogen measured at different times was used as the targ et spectrum to evaluate the model , after comparing with the trainin g data , the matching absorption spectrum was obtained , and the re cognition rate reached 97.34% . The recognition results fully indica te that the identification of different kinds of pathogens can be reco gnized by Siamese neural network , which provides an effective met hod of the detection and identification of pathogens by terahertz spe ctroscopy .