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Synchronizability of dynamical networks can be defined as the ease by which the network synchronizes its activity. We propose a method for enhancing the synchronizability of dynamical networks by efficient rewirings. The method is based on the eigenvectors corresponding to the second smallest and the largest eigenvalue of the Laplacian matrix and a modified version of the simulated annealing approach...
We present spectral matting: a new approach to natural image matting that automatically computes a basis set of fuzzy matting components from the smallest eigenvectors of a suitably defined Laplacian matrix. Thus, our approach extends spectral segmentation techniques, whose goal is to extract hard segments, to the extraction of soft matting components. These components may then be used as building...
Over the last years computer vision researchers have shown great interest for the so called spectral clustering, where the data are clustered analysing the first few eigenvectors (i.e., the ones relative to the first eigenvalues) of a the Laplacian matrix, derived directly from the data-set. Note that for the purpose of data clustering the eigenvectors need not to be determined accurately. When clustering...
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