The subject of this dissertation is to show how learning can be used for multidimensional signal processing, in particular computer vision. Learning is a wide concept, but it can generally be defined as a system’s change of behaviour in order to improve its performance in some sense. Learning systems can be divided into three classes: supervised learning, reinforcement learning and unsupervised...

Broadband wireless channels, where high data rates are transmitted, are extremely dispersive in nature. A fundamental challenge in the design of equalizers for the broadband case lies in reducing complexity. Broadband finite impulse response (FIR) beamformers employ a space-time antenna array which reduces the multipath delay spread to narrowband levels. The beamformers should additionally pres...

design methods for paraunitary matrices from complete orthogonal sets of idempotents and related matrix structures are presented. these include techniques for designing non-separable multidimensional paraunitary matrices. properties of the structures are obtained and proofs given. paraunitary matrices play a central role in signal processing, in particular in the areas of filterbanks and wavelets.

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