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The main purpose of this paper is the development of a constrained optimal boundary state estimation framework for the dissipative systems with boundary control and boundary observation operator. These dissipative systems will be described by an extended system which involves no unbounded operator except for the system's dynamics generator through the change of variables and Yosida approximation....
Recently, spectral clustering has wide application in pattern recognition and data mining because it can obtain global optima solution and adapt to sample spaces with any shape. Thus, a spectral clustering algorithm based on normalized cuts is proposed in this paper. It selects the k eigenvalues and corresponding eigenvectors of a given stochastic matrix and clusters in n times k sub-space. Experimental...
Outlier detection is widely used for many areas such as credit card fraud detection, discovery of criminal activities in electronic commerce, weather prediction and marketing. In this paper, we demonstrate the effectiveness of spectral clustering in dataset with outliers. Through spectral method we can use the information of feature space with eigenvectors rather than that of the whole dataset to...
Spectral clustering has become one of the most popular modern clustering algorithms because it has "global" optimal solution compared with traditional clustering methods. In this paper, we propose a modified NJW algorithm which is based on matrix perturbation theory and can be easily implemented. In addition, the algorithm can estimate the parameter k and in turn achieve appropriate clusters...
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