Enhanced T-ray signal classification using wavelet preprocessing
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- Yin, X.X., Kong, K.M., Lim, J.W. et al. Med Bio Eng Comput (2007) 45: 611. doi:10.1007/s11517-007-0185-y
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This study demonstrates the application of one-dimensional discrete wavelet transforms in the classification of T-ray pulsed signals. Fast Fourier transforms (FFTs) are used as a feature extraction tool and a Mahalanobis distance classifier is employed for classification. Soft threshold wavelet shrinkage de-noising is used and plays an important role in de-noising and reconstruction of T-ray pulsed signals. An iterative algorithm is applied to obtain three optimal frequency components and to achieve preferred classification performance.