Description: Study of wavelet concepts.  Use wavelet-based filter banks
	to process signals.

Textbook:  G. Strang and T. Nguyen, Wavelets and Filter Banks, Wellesley-
        Cambridge Press, MA, 1996.
        
     Chapter                 Topic

        1       Introduction: Overview and notation.

        2       Filters: Sampling, time-invariance, ideal filters, Fourier
                analysis, bases and frames; time, frequency, and scaling.

        3       Downscaling and Unscaling: Matrices, subsampling in
                frequency domain, z-domain; sampling interchange.

        4       Filter Banks: Perfect reconstruction, polyphase matrix,
                efficient filter banks, upsampling and reconstruction,
                lattice structure.

        5       Orthogonal Filter Banks: Paraunity matrices, orthonormal
                filter banks, halfband filters, spectral factorizaiton,
                Daubechies filters.

        6       Multiresolution: Wavelets from filters, scaling function by
                recursion, infinite product formula, biorthogonal wavelets.

        7       Wavelet Theory: Accuracy, cascaade algorithm, smoothness,
                splines and semiorthogonal wavelets, multifilters and wavelets.

        8       Finite Length Signals: Circular convolution, symmetric
                extension, cosine bases and DCT, smooth local cosine bases,
                boundary filters and wavelets.

        9       M-Channel Filter Banks: Freedom versus structure, polyphase
                form, perfect reconstruction, cosine-modulated filter banks,
                multidimensional filters and wavelets.

        10      Design Methods: Distortions, general perspective, perfect
                reconstruction, two-channel filter banks, cosine-modulated
                filter banks.

        11      Applications: Fingerprints, image and video compression;
                speech, audio, and ECG compression; shrinkage, denoising,
                and feature detection; communcation applications, wavelet
                integrals for differential equations.


Project: Design, analyze, and test wavelet and filter algorithms to
	characterize standard library signals.
 
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