Discrete Representation of Signals from Infinite Dimensional Hilbert Spaces with Application to Noise Suppression and Compression
MARYLAND UNIV COLLEGE PARK INST FOR SYSTEMS RESEARCH
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Addressed in this thesis is the issue of representing signals from infinite dimensional Hilbert spaces in a discrete form. The discrete representations which are studied come from the irregular samples of a signal dependent transform called the group representation transform, e.g., the wavelet and Gabor transforms. The main issues dealt with are i the recoverability of a signal from its discrete representation, ii the suppression of noise in a corrupted signal, and iii compression through efficient discrete representation.
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