In order to utilize the repetitive information among the video sequence more reasonably, this paper proposes an image mosaicing approach based on space-time manifolds for the video sequence taking the properties of hi...
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ISBN:
(纸本)9787894631046
In order to utilize the repetitive information among the video sequence more reasonably, this paper proposes an image mosaicing approach based on space-time manifolds for the video sequence taking the properties of high-overlapped ratio between neighbor frames and multiple frames into account. Firstly, we iterate Lucas-Kanade optical flow under Gaussian pyramid strategy to compute the motion parameters between neighbor frames with higher accuracy and align the sequence, in the meantime, eliminate the brightness difference among the neighbors combining with the result of motion computation, and then stitch together the whole sequence whose brightness is already uniform into a high resolution image using the space-time manifolds mosaicing technique. It was verified by the experiment that the proposed approach was very effective to video sequences and the mosaicing result was nice.
Angle random walk (ARW) is the noise component at the output of a fiber optic gyroscope (FOG) and it affects the FOG short-term accuracy. Using only the noise property described by random walk coefficient, we develope...
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ISBN:
(纸本)9787894631046
Angle random walk (ARW) is the noise component at the output of a fiber optic gyroscope (FOG) and it affects the FOG short-term accuracy. Using only the noise property described by random walk coefficient, we developed an unsupervised adaptive filter (UAF) for suppressing the noise. Theoretical analysis illuminates that UAF performs as good as the best FIR filter in the sense of means square. Experimental results both in stationary and non-stationary cases show that UAF is more effective than wavelet denoising and that based on fast fourier transform.
EEG data can be easily influenced by other components in the process of recording, which would thus interfere the analysis. Independent Component Analysis (ICA) is a valid method for blind source separation. It can es...
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ISBN:
(纸本)9787894631046
EEG data can be easily influenced by other components in the process of recording, which would thus interfere the analysis. Independent Component Analysis (ICA) is a valid method for blind source separation. It can estimate original signals' independent components from observed signals even the original signals and mixing model are unknown. Considering the shortcomings of the application of two ICA algorithms, FastICA and extended Infomax, to EEG artifacts removal, we propose a novel InfastICA algorithm by combing FastICA and extended Infomax. By appling to removal of the EOG artifacts from EEG, test results show that this new algorithm has no special requests to the matrix W's default values and study steps, and has a fast convergence speed, with simple operation and practical application.
As the trend of future space based information system, networked space based information system can acquire and process all sorts of information more quickly and continuously under the user task scheduling. In the bac...
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ISBN:
(纸本)9787894631046
As the trend of future space based information system, networked space based information system can acquire and process all sorts of information more quickly and continuously under the user task scheduling. In the background of earthquake relief for applications, working flow and main tasks of the system are analyzed, and continuity effectiveness evaluation index system is constructed in multi-task level. The continuity effectiveness is a measurement of intensive degree of information returned. Evaluation model based on grey evaluation method is constructed and different reference indexes are used for different tasks. Examples are given by using statistical data in simulation, and the integrative evaluation results are obtained. Detailed evaluation results in every specific task level are offered, which are helpful to find out the effectiveness bottleneck factors meanwhile provide guidance in system design and development.
A novel modeling method of T-S fuzzy system for an affine nonlinear system is proposed. Based on this method, the responses of T-S fuzzy system is the same as the original nonlinear, the modeling error is avoided comp...
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A novel modeling method of T-S fuzzy system for an affine nonlinear system is proposed. Based on this method, the responses of T-S fuzzy system is the same as the original nonlinear, the modeling error is avoided compared with the linearization method around the equilibrium points, and this method can be applied the nonlinear system contained the multiple nonlinear terms. T-S fuzzy model of GMAW system is established, the response characteristics of the T-S fuzzy system are not changed compared with the nonlinear GMAW system. The simulation result proves the validity of this method.
Malaria is one of the most serious parasitic infections of human. The accurate and timely diagnosis of malaria infection is essential to control and cure the disease. Some image processing algorithms to automate the d...
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Malaria is one of the most serious parasitic infections of human. The accurate and timely diagnosis of malaria infection is essential to control and cure the disease. Some image processing algorithms to automate the diagnosis of malaria on thin blood smears are developed, but the percentage of parasitaemia is often not as precise as manual count. One reason resulting in this error is ignoring the cells at the borders of images. In order to solve this problem, a kind of diagnosis scheme within large field of view (FOV) is proposed. It includes three steps. The first step is image mosaicing to obtain large FOV based on space-time manifolds. The second step is the segmentation of erythrocytes where an improved Hough Transform is used. The third step is the detection of nucleated components. At last, it is concluded that the counting accuracy of malaria infection within large FOV is finer than several regular FOVs.
In order to describe precisely the dynamics and friction nonlinearity of servo systems, a novel direct identification method for nonlinear continuous model is proposed. The sampled input-output data and logic data cor...
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In order to describe precisely the dynamics and friction nonlinearity of servo systems, a novel direct identification method for nonlinear continuous model is proposed. The sampled input-output data and logic data corresponding to the velocity direction are chosen as the identification data. Through equivalent transformation, the unknown parameters are removed to the linear part of the model. Then the identification method based on state variable filter is utilized to determine the unknown parameters. Subsequently, the nonlinear continuous model of the servo system is obtained. The effectiveness of the proposed method is demonstrated by simulations and identification experiments on the two axis servo table. Both the simulations and experimental results show that, with the proposed method, the accurate nonlinear continuous model can be obtained even under sensor noises, which gives an accurate description of the system dynamics.
In this paper an Ad hoc networks are established for the communication among unmanned air vehicle (UAV) group corporation. It is brought out that reference point group mobility model (RPGM) could simulate the behavior...
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In this paper an Ad hoc networks are established for the communication among unmanned air vehicle (UAV) group corporation. It is brought out that reference point group mobility model (RPGM) could simulate the behavior of UAV group to analyze the efficiency of router algorithms as to the movement of UAV node. The result shows that the Ad hoc networks can solve the communication problem of UAV group, and also find out that the ADOV algorithm has data large throughout and more adaptive to the variation of topology, the DSR has a lighter routing load. The efficiency of router algorithm also changes as to the node speed. As a result the routing algorithm should be chosen according to the different tactical mission of UAV group, and the designs of corporation method should consider the changing of network efficiency as to node moving speed.
Compressive sensing is a revolutionary idea proposed recently to achieve much lower sampling rate for signals. In the image application with limited resources the camera data can be stored and processed in compressed ...
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Compressive sensing is a revolutionary idea proposed recently to achieve much lower sampling rate for signals. In the image application with limited resources the camera data can be stored and processed in compressed form. An algorithm for moving object and region detection in video using a compressive sampling is developed. The algorithm estimates motion information of the moving object and regions in the video from the compressive measurements of the current image and background *** algorithm does not perform inverse compressive operation to obtain the actual pixels of the current image nor the estimated background. This leads to a computationally efficient method and a system compared with the existing motion estimation *** experimental results show that the sampling rate can reduce to 25% without sacrificing performance.
The dynamic weapon-target assignment （DWTA） problem is an important issue in the field of military command and control. An asset-based DWTA optimization model was proposed with four kinds of constraints considered, ...
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The dynamic weapon-target assignment （DWTA） problem is an important issue in the field of military command and control. An asset-based DWTA optimization model was proposed with four kinds of constraints considered, including capability constraints, strategy constraints, resource constraints and engagement feasibility constraints. A general ＂virtual＂ representation of decisions was presented to facilitate the generation of feasible decisions. The representation is in essence the permutation of all assignment pairs. A construction procedure converts the permutations into real feasible decisions. In order to solve this problem, three evolutionary decision-making algorithms, including a genetic algorithm and two memetic algorithms, were developed. Experimental results show that the memetic algorithm based on greedy local search can generate obviously better DWTA decisions, especially for large-scale problems, than the genetic algorithm and the memetic algorithm based on steepest local search.
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