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Classification of the Transient Signals via Auditory Representations
We use a model of processing in the human auditory system to develop robust representations of signals. These reduced representations are then presented to a neural network for training and classification.<P>Empirical ...
Discrete Representation of Signals from Infinite Dimensional Hilbert Spaces with Applications to Noise Suppression and Compression
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 ...