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Regularized empirical risk minimization including support vector machines plays an important role in machine learning theory. In this paper regularized pairwise learning (RPL) methods based on kernels will be investigated. One example is regularized minimization of the error entropy loss which has recently attracted quite some interest from the viewpoint of consistency and learning rates. This paper...
In this paper, a wavelet-based neural network (WNN) is introduced for nonlinear system identification. The structure of the WNN is similar to that of multi-layer perceptron (MLP), except that here the activation function of the hidden nodes is replaced by a wavelet function. It will be proved that any function f ∊ L2(Rn) can be approximated on any bounded domain by the WNN. Employing the MLP-like...
According to the research on node centrality of complex network, the existing methods although take the global and local importance of node into account, but don't consider the importance of adjacent edges and the direction of interaction. For this, provides a new method for measuring the node centrality of complex directed network, considers the node's role in network efficiency and degree distribution...
Feedback stabilization of boiler-turbine system is discussed by using finite time control technique. First, boiler-turbine system is state feedback linearized. Then, by virtue of finite time control technique, series controllers and parallel controllers are designed respectively to stabilize boiler-turbine system. The closed-loop system exhibits faster convergence, better robustness and disturbance...
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