Transformer is the most critical equipment in the power system. In recent years, secondary silicon steel sheets have been used in the manufacture of transformer cores, which has caused hidden dangers in the quality of...
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This paper presents an improved equivalent-input-disturbance(EID) approach to deal with periodic disturbances. The approach has two degrees of freedom. One is an improved EID compensator, in which a repetitive control...
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This paper presents an improved equivalent-input-disturbance(EID) approach to deal with periodic disturbances. The approach has two degrees of freedom. One is an improved EID compensator, in which a repetitive controller is inserted in this study. The other is a conventional servo system for a reference *** improved EID compensator estimates and compensates for periodic disturbances without steady-state error, and the servo system ensures a satisfactory tracking performance. The improved EID compensator is designed using the linear-matrix-inequality(LMI) method. Three parameters in an LMI are selected using the particle-swarm-optimization(PSO) algorithm. The state-feedback gain of the conventional servo system is designed using the linear-quadratic-regulator(LQR) method. Simulation results of a rotational control system demonstrate the validity of the approach and its advantage over others.
In recent visual tracking research,correlation filter(CF)based trackers become popular because of their high speed and considerable *** methods mainly work on the extension of features and the solution of the boundary...
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In recent visual tracking research,correlation filter(CF)based trackers become popular because of their high speed and considerable *** methods mainly work on the extension of features and the solution of the boundary effect to learn a better correlation ***,the related studies are *** exploring the potential of trackers in these two aspects,a novel adaptive padding correlation filter(APCF)with feature group fusion is proposed for robust visual tracking in this paper based on the popular context-aware tracking *** the tracker,three feature groups are fused by use of the weighted sum of the normalized response maps,to alleviate the risk of drift caused by the extreme change of single ***,to improve the adaptive ability of padding for the filter training of different object shapes,the best padding is selected from the preset pool according to tracking precision over the whole video,where tracking precision is predicted according to the prediction model trained by use of the sequence features of the first several *** sequence features include three traditional features and eight newly constructed *** experiments demonstrate that the proposed tracker is superior to most state-of-the-art correlation filter based trackers and has a stable improvement compared to the basic trackers.
With increasing people who suffer from diet-related diseases, providing suggestions for personal daily nutrient-dense intake is highly expected. However, current dietary nutrition models are less precise, and dietary ...
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This paper presents a high-precision control method based on the model-following control (MFC) and equivalent-input-disturbance (EID) approaches. The MFC approach ensures that the output of the plant tracks the output...
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It is important to predict microbe-disease associations, as it helps to understand the cause of diseases episodes, the prevention of diseases, among other roles. Traditionally, the study of microbe-disease association...
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With the development of science and technology,graph convolutional network has made great progress in improving the accuracy of action ***,there still exists some deficiencies in current ***,the human skeleton point c...
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ISBN:
(数字)9789887581536
ISBN:
(纸本)9781665482561
With the development of science and technology,graph convolutional network has made great progress in improving the accuracy of action ***,there still exists some deficiencies in current ***,the human skeleton point coordinates entering into the network are barely refined,which may cause large ***,the second-order information(the length and direction of bones),which can reflect action characteristics discriminatively,is rarely *** solve the above issues,a two stream graph convolutional network with pose refinement for skeleton based action recognition is ***,we use an adaptive block to to help improve the *** test our method on Kinetics dataset and the experiment show it can get better results than some recent methods,which plays a positive role in future research.
In this paper, we propose a dual polarization dual mode 3dB beam splitter. By utilizing the shallow etched multimode interference (MMI) coupler, the proposed device can handle TE 0 , TE 1 , TM 0 and TM 1 modes simul...
In this paper, we propose a dual polarization dual mode 3dB beam splitter. By utilizing the shallow etched multimode interference (MMI) coupler, the proposed device can handle TE 0 , TE 1 , TM 0 and TM 1 modes simultaneously.
Convolutional neural network compression technology plays an extremely important role in model transplantation and deployment, especially in mobile and embedded hardware platforms with small memory and low computing p...
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Convolutional neural network compression technology plays an extremely important role in model transplantation and deployment, especially in mobile and embedded hardware platforms with small memory and low computing power, compression technology is even more critical. Convolutional neural network channel pruning technology has developed rapidly in recent years, and a number of excellent pruning algorithms have emerged. The channel pruning technology has gradually developed from the earliest static pruning to dynamic pruning, which adopts different pruning schemes for different inputs. However, the current dynamic pruning scheme needs to introduce multiple modules to predict the mask to prune the feature maps, and some schemes also introduce multiple hyperparameters in the loss function to balance the model accuracy and pruning rate, which leads to The model has difficulty converging during training. We propose a dynamic pruning method, each convolution structure configures a simple prediction module, and generating dynamic labels through the input's norm and similarity to guide the prediction module training, which will not bring new parameters to the loss function. We conducted related experiments on multiple models on the Cifar10 datasets. The experiments on ResNet56 show that our scheme is 1.3% higher than the most advanced scheme in terms of compression rate under the premise of the same accuracy.
We propose and demonstrate a polarization-independent dual mode spot size converter (SSC) on silicon integrated platform. By utilizing gradual index distributed subwavelength gratings (GRIN-SWG). The proposed device c...
We propose and demonstrate a polarization-independent dual mode spot size converter (SSC) on silicon integrated platform. By utilizing gradual index distributed subwavelength gratings (GRIN-SWG). The proposed device can be used in the chip-level PDM-MDM system.
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