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In least squares support vector machine (LS-SVM), nonlinear function estimation is done by solving a linear set of equations instead of solving a quadratic programming problem, and a non-sparse solution is obtained yet. Several sparse algorithms have been developed to obtain reduced support vectors to improve the generalization performance of LS-SVM. In this paper, we proposed a sparse method based...
The new Binary Offset Carrier (BOC) modulated signals, where the pseudo random noise (PRN) code is multiplied with rectangular subcarriers, split the spectrum symmetrically and reduce interference with existing navigation signals. In spite of these benefits of the Autocorrelation Function (ACF) for BOC signals, e.g. better multipath mitigation and sharper correlation main peak for better tracking...
Outlier detection is an important procedure in industrial dataset preprocess to guarantee the industrial process operating normally. This paper proposed a new local density definition in the basis of the minimum hyper sphere for outlier mining algorithm. First, the novel local k-density definition of an object is proposed by using the minimum enclosing hyper sphere algorithm. After this, the new k-density...
Discretization algorithms have played an important role in data mining, which is widely applied in industrial control. Since the current discretization methods can not accurately reflect the degree of the class-attribute interdependency of the industrial database, a new discretization algorithm, which is based on information distance criterion and ant colony optimization algorithm(ACO), is proposed...
Outlier mining is an important work of data mining and a density-similarity-neighbor based outlier factor (DSNOF) algorithm is proposed to indicate the degree of outlier-ness of an object. The proposed algorithm calculates the densities of an object and its neighbors and constructs the similar density series (SDS) in the neighborhood of the object. Based on the SDS, the proposed algorithm computes...
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