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Author Yin, X. X. ♦ Ng, B. W. -H. ♦ Ferguson, B. ♦ Mickan, S. P. ♦ Abbott, D.
Source CiteSeerX
Content type Text
File Format PDF
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword T-ray Pulse ♦ Wavelet Transforms ♦ Statistical Model ♦ Decomposed Terahertz ♦ Mail Packaging Inspection ♦ Biomedical Diagnosis ♦ Correlation Method ♦ Test Sample ♦ Auto Regressive ♦ Human Osteosarcoma ♦ T-ray Classification System ♦ Improved Prony Method ♦ Arma Model Parameter ♦ Auto Regressive Moving Average ♦ Heterogeneous Layer ♦ Different Powder Sample ♦ Normal Human Bone
Abstract This study applies Auto Regressive (AR) and Auto Regressive Moving Average (ARMA) modeling to wavelet decomposed terahertz pulsed signals to assist biomedical diagnosis and mail/packaging inspection. T-ray classification systems supply a wealth of infor-mation about test samples to make possible the dis-crimination of heterogeneous layers within an object. In this paper, the classification of normal human bone (NHB) osteoblasts against human osteosarcoma (HOS) cells and the identification of seven different powder samples are demonstrated. A correlation method and an improved Prony’s method are investigated in the calculation of the AR and ARMA model parameters. These parameters are obtained for models from second
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research
Education Level UG and PG ♦ Career/Technical Study