The present work focuses on the node deployment algorithm of Wireless Sensor Networks. The Central Voronoi Tessellation algorithm is employed to optimize the node position. The energy consumption of the whole sensor n...
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The present work focuses on the node deployment algorithm of Wireless Sensor Networks. The Central Voronoi Tessellation algorithm is employed to optimize the node position. The energy consumption of the whole sensor network will be minimized by using this algorithm. Simulation of the proposed algorithm shows the effectiveness of minimizing the energy consumption.
Virtual Reality Head-Mounted Display (HMD), also known as VR glasses, is a typical amusement device that provides an immersive viewing experience based on virtual reality technology in cultural tourism equipment. Vari...
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Stage lighting design is an important step in the visual effect configuration scheme of small cultural complex. This paper mainly discusses the lighting configuration of small space with multi-functional art services ...
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Terrain perception in complex environment is important for Autonomous Land Vehicle to drive automatically. In order to access the terrain information, in this paper, we present a terrain perception method based on Hid...
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Terrain perception in complex environment is important for Autonomous Land Vehicle to drive automatically. In order to access the terrain information, in this paper, we present a terrain perception method based on Hidden Markov Model (HMM) which combines LIDAR with machine vision. On the basis of spatial fan-shaped model, terrain feature extraction is performed to acquire the observation model. Hidden markov models describe the vertical structure of the driving space and Viterbi algorithm is used for terrain classification. Then the navigation decision is given based on the perception of the complex environment. Experiment results show that the method can give an accurate environment description for ALV.
This paper aims at reducing the calibration effort of EEG-based brain-computer interfaces (BCIs). More specifically, in the context of cross-subject classification, we correct covariate shift of EEG data from differen...
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ISBN:
(纸本)9781728145709
This paper aims at reducing the calibration effort of EEG-based brain-computer interfaces (BCIs). More specifically, in the context of cross-subject classification, we correct covariate shift of EEG data from different subjects, so that a classifier trained on auxiliary subjects can also be applied to a new subject, without any labeled trials from the new subject. Methods: We propose two approaches to enhance the performance of a state-of-the-art Riemannian space transfer learning (TL) algorithm: 1) trials selection, which resamples trials from the auxiliary subjects so that they become more consistent with those of the new subject;and, 2) channel selection, which reduces the number of channels and hence makes the Riemannian space computations more accurate and efficient. Results: We tested the proposed approaches on two motor imagery datasets. The results verified that they can enhance the performance of the state-of-the-art TL algorithm. Conclusion and significance: Our proposed approaches make the state-of-the-art TL algorithm more effective and efficient.
With the development of society, network security becomes more and more important. It is inevitable to establish the risk index system to effectively monitor the security of network. In the previous study, due to abse...
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This paper presents a general six degrees of freedom(6-DOF) robot arm control system based on Linux and field-programmable gate array(FPGA).The system provides a friendly human-computer interaction *** can complete pa...
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This paper presents a general six degrees of freedom(6-DOF) robot arm control system based on Linux and field-programmable gate array(FPGA).The system provides a friendly human-computer interaction *** can complete palletizing,handling and other processes through simple programming of the interactive *** adopt industrial personal computer(IPC) as the controller to accomplish the kinematics calculation,design motion control board connected with the controller and the servo system,and use the servo system to implement the motion of the robot *** kinematics calculation and trajectory generation based on cubic polynomial are developed based on the Linux system,which improves the portability of the *** a normal method is adopted in updating trajectory points to improve *** control board is designed based on FPGA,which with the characteristic of parallel computing raises the running speed of the robot arm.
Detecting the lithium battery surface defects is a difficult task due to the illumination reflection from the surface. To overcome the issue related to labeling and training big data by using 2D techniques, a 3D point...
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This paper presents an adaptive robust dynamic surface control (ARDSC) algorithm for the position control of DC torque motors which are modeled as third-order nonlinear systems with parametric and nonlinear uncertaint...
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ISBN:
(纸本)9781424474264
This paper presents an adaptive robust dynamic surface control (ARDSC) algorithm for the position control of DC torque motors which are modeled as third-order nonlinear systems with parametric and nonlinear uncertainties. Based on the dynamic surface control (DSC) approach, the "explosion of terms" problem in the normal adaptive robust control (ARC) is avoided, which enhances the practicability of the controller. Furthermore, besides theoretically proving that the tracking error is uniformly ultimate bounded or asymptotically converge to zero in presence of parametric uncertainties only, the true estimates of the unknown parameters are achieved by designing a novel adaptation law, which improves the system performance and can be used in system monitor and diagnosis on-line as byproducts. Finally, the comparative simulation results illustrate that the proposed algorithm is very effective.
In this paper,a novel particle swarm algorithm for solving constrained multiobjective optimization problems is *** new algorithm is able to utilize valuable information from the infeasible region by intentionally keep...
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ISBN:
(纸本)9781479947249
In this paper,a novel particle swarm algorithm for solving constrained multiobjective optimization problems is *** new algorithm is able to utilize valuable information from the infeasible region by intentionally keeping a set of infeasible solutions in each *** enhance the diversity of these preserved infeasible solutions,a modified version of adaptive grid is *** addition,a voting mechanism is designed to balance the preference of infeasible solutions with smaller constraint violation and the exploration of the infeasible *** effectiveness of the proposed method is validated by simulations on several commonly used benchmark *** using the hypervolume indicator,it is shown that the proposed algorithm is more powerful than two other state-of-the-art algorithms.
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