Abstract

Although the number of representation subspaces is large, only few ones will contain data samples from sensor measurements. By identifying these few subspaces, we find the representation in the reduced space. We describe sparse representation and dictionary learning methods. Finally there is the experiment of the application of dictionary learning. The main focus of this thesis is the dictionary learning theory and experimental results show that the algorithm is effective.

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