Type of Document	Thesis
Author	Sripathi, Deepika
Author's Email Address	dipikareddy@hotmail.com
URN	etd-11242003-185039
Title	Efficient Implementations of Discrete Wavelet Transforms Using FPGAs
Degree	Master of Science
Department	Electrical and Computer Engineering, Department of
Advisory Committee	Advisor Name Title Dr. Simon Y. Foo Committee Chair Dr. Anke Meyer-Baese Committee Member Dr. Uwe Meyer-Baese Committee Member
Keywords	distributed arithmetic DWT
Date of Defense	2003-11-18
Availability	unrestricted
Abstract Recently the Wavelet Transform has gained a lot of popularity in the field of signal processing. This is due to its capability of providing both time and frequency information simultaneously, hence giving a time-frequency representation of the signal. The traditional Fourier Transform can only provide spectral information about a signal. Moreover, the Fourier method only works for stationary signals. In many real world applications, the signals are non-stationary. One solution for processing non-stationary signals is the Wavelet Transform. Currently, there is tremendous focus on the application of Wavelet Transforms for real-time signal processing. This leads to the demand for efficient architectures for the implementation of Wavelet Transforms. Due to the demand for portable devices and real-time applications, the design has to be realized with very low power consumption and a high throughput. In this thesis, different architectures for the Discrete Wavelet Transform filter banks are presented. The architectures are implemented using Field Programmable Gate Array devices. Design criteria such as area, throughput and power consumption are examined for each of the architectures so that an optimum architecture can be chosen based on the application requirements. In our case study, a Daubechies 4-tap orthogonal filter bank and a Daubechies 9/7-tap biorthogonal filter bank are implemented and their results are discussed. Finally, a scalable architecture for the computation of a three-level Discrete Wavelet Transform along with its implementation using the Daubechies length-4 filter banks is presented.
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