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Subspace learning has been widely used in signal processing, machine learning, computer vision and so on. Matrix rank minimizing is a fundamental model. Nuclear norm is a convex relaxation for rank minimizing. In this paper, we propose a polynomial function to smoothen the nuclear norm. Lagrange multipliers method is employed to solve the problem. The optimal solution is obtained by iterative procedure...
A simple tuning method for second-order active disturbance rejection control (ADRC) that achieves high performance and good robustness for a wide range of processes is presented. ADRC is a novel control strategy whose exciting performance has been shown by literatures. The proposed method makes ADRC become easy to tune and more practical. Once the desired settling time is given, only one parameter...
Quantum key distribution (QKD) has been proved unconditionally secure. But noise and imperfection of realistic devices are major difficulties for implementing quantum key distribution. Particularly, the birefringence in optical fiber corresponds to an insuppressible collective unitary transformation on the polarization space. Obviously does not change the permutation symmetry of multiphoton state...
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