Yin, X.Kong, K.Lim, J.Ng, B.Ferguson, B.Mickan, S.Abbott, D.2007-11-282007-11-282007Medical and Biological Engineering and Computing, 2007; 45(6):611-6160140-01181741-0444http://hdl.handle.net/2440/39634The original publication is available at www.springerlink.comThis 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.enMahalanobis distance classifierWavelet denoisingT-raysJournal article00200709372007112816113110.1007/s11517-007-0185-y0002472119000112-s2.0-3425018813348741Ng, B. [0000-0002-8316-4996]Abbott, D. [0000-0002-0945-2674]