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A distributed antenna system (DAS) architecture is considered to be a key enabler for further Network Virtualization where different network configurations are created as needed by a centralized decision making unit that is typically integrated into the Cloud Radio Access Networks (C-RAN) which offers a potential architecture for 5G wireless communication systems. Many schemes have been proposed for...
In this paper, in order to solve the dimension problem in over-parameterized method (OPM) and the rank constraint problem in subspace identification method (SIM), The nuclear norm subspace identification method (N2SID) is proposed with a combination of nuclear norm minimization (NNM) and least-parameterized method (LPM). NNM is a heuristic convex relaxation of the rank minimization, and preprocesses...
Motion capture is widely used in sports, entertainment and medical applications. An important issue is to recover motion capture data that has been corrupted by noise and missing data entries during acquisition. In this paper, we propose a new method to recover corrupted motion capture data through trajectory-based sparse representation. The data is firstly represented as trajectories with fixed length...
Poisson disk sampling has excellent spatial and spectral properties, and plays an important role in a variety of visual computing. Although many promising algorithms have been proposed for multidimensional sampling in euclidean space, very few studies have been reported with regard to the problem of generating Poisson disks on surfaces due to the complicated nature of the surface. This paper presents...
Learning from data sets that contain very few instances of the minority class usually produces biased classifiers that have a higher predictive accuracy over the majority class, but poorer predictive accuracy over the minority class. SMOTE (synthetic minority over-sampling technique) is specifically designed for learning from imbalanced data sets. This paper presents a modified approach (MSMOTE) for...
In practical application, the statistical characteristics of signal and noise are usually unknown or can't have been learned so that we hardly design fix coefficient digital filter. In allusion to this problem, the theory of the adaptive filter and adaptive noise cancellation are researched deeply in the thesis. According to the LMS and the RLS algorithms realize the design and simulation of adaptive...
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