"Signal identification based on different sensing systems like microwaves, infra-red, x-rays and terahertz waves is one of the classic problems in signal processing. Earlier methods had relied mainly on the amplitude spectrum obtained by these sensing techniques mainly due to non-availability of the phase information for the signals. Most of them are based on techniques like absorbance spectrum that requires a reference material's signal for the test material's identification. They are also sensitive to noise and highly dependent on the peak detection algorithms. Modern equipments with both amplitude and phase information provide an opportunity for time-domain signal based methods that had not been used earlier. In this thesis, the information available through time-domain signals is utilized by the use of different wavelet transform based methods. The methods have been tested for data obtained through the terahertz time-domain spectroscopy (THz-TDS), particularly because of their ability to capture the distinguishing features of the material. The methods presented here are based on the Continuous and the Discrete Wavelet Transforms. The wavelet transforms have been used to calculate time-frequency energy density in the scale-shift domain. These energy densities have then been used to identify the features described as maxima lines and ridges that are used as features for the purpose of material identification. The methods are found to be useful in the presence of noise require no pre-filtering of the signals as required in most conventional material identification techniques. They also provide a scalable method for increasing accuracy based on the computational power available. All the simulations have been done on MATLAB"--Abstract, page iii.
Rao, Vittal S.
Moss, Randy Hays, 1953-
Electrical and Computer Engineering
M.S. in Electrical Engineering
Missouri University of Science and Technology
ix, 48 pages
© 2010 Rajat Pashine, All rights reserved.
Thesis - Open Access
Library of Congress Subject Headings
Signals and signaling
Print OCLC #
Electronic OCLC #
Link to Catalog Recordhttp://laurel.lso.missouri.edu/record=b8034739~S5
Pashine, Rajat, "Signal analysis for multiple target materials through wavelet transforms" (2010). Masters Theses. 4799.