This paper systematically studies the problem of decision rule acquisition in inconsistent incomplete decision systems (IIDSs). First, a tolerance granular framework model based on tolerance granular computing is pres...
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In this paper, we present a pose based approach for locating and recognizing human actions in videos. In our method, human poses are detected and represented based on deformable part model. To our knowledge, this is t...
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Content-aware music adaption, i.e. music resizing, in temporal constraints starts drawing attention from multimedia communities because of the need of real-world scenarios, e.g. animation production and radio advertis...
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Ensemble learning with output from multiple supervised and unsupervised models aims to improve the classification accuracy of supervised model ensemble by jointly considering the grouping results from unsupervised mod...
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ISBN:
(纸本)9781577355120
Ensemble learning with output from multiple supervised and unsupervised models aims to improve the classification accuracy of supervised model ensemble by jointly considering the grouping results from unsupervised models. In this paper we cast this ensemble task as an unconstrained probabilistic embedding problem. Specifically, we assume both objects and classes/clusters have latent coordinates without constraints in a D-dimensional Euclidean space, and consider the mapping from the embedded space into the space of results from supervised and unsupervised models as a probabilistic generative process. The prediction of an object is then determined by the distances between the object and the classes in the embedded space. A solution of this embedding can be obtained using the quasi-Newton method, resulting in the objects and classes/clusters with high co-occurrence weights being embedded close. We demonstrate the benefits of this unconstrained embedding method by three real applications.
Non-negative Matrix Factorization (NMF) is one latest presented approach for obtaining document clusters, which aimed to provide a minimum error non-negative representation of the term-document matrix. In this paper, ...
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People often feel the limitation of time to read the continuously increasing articles they need to read. It is a grand challenge to handle the explosion of articles. To understand how humans read articles and get the ...
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Aim to solve the poor dynamic performance and the low disturbance resistance of PI power decoupling controller for DFIG power generator system based on matrix converter, this paper propose a nonlinear control algorith...
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Aim to solve the poor dynamic performance and the low disturbance resistance of PI power decoupling controller for DFIG power generator system based on matrix converter, this paper propose a nonlinear control algorithm for the AC-excitation DFIG system. First, we establish the mathematical model of the DFIG, based on the model, use the inverse system theory and deduce the inverse model, add the inverse model in series to the front of the original system model, develop the whole system to a pseudo linear system. Consider the system performance influenced by the parameters of the linearized model, we use the predictive control to improve the robustness. The simulation results show that the control strategy has fast response and good dynamic performance. The off-grid and cut-grid experimental data validate that under sub-synchronous or super-synchronous state, the stator voltage and frequency can maintain stability and achieve variable speed constant frequency operation.
The electromagnetic waves propagation situation is very complex in mine tunnels, so it is important to establish an efficient MIMO channel model for applying wireless communication technology to coal mine underground....
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In image/video processing software and hardware products, low complexity interpolation algorithms, such as cubic and splines methods, are commonly used. However, these methods tend to blur textures and produce jaggy e...
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