Landing footprint of an entry vehicle provides critical information for mission planning. Conventional methods calculate it through solving a family of multi-constraints optimal control problems. It is difficult to so...
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Ensemble learning aggregates outputs from multiple base learners for better performance. Bootstrap aggregating (bagging) and boosting are two popular such approaches. They are suitable for integrating unstable base le...
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Unlike in the 1D case, it is not always possible to find a minimal state-space realization for a 2D system except for some particular categories. The purpose of this paper is to explore a constructive approach to the ...
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Unlike in the 1D case, it is not always possible to find a minimal state-space realization for a 2D system except for some particular categories. The purpose of this paper is to explore a constructive approach to the minimal Roesser model realization problem for a class of 2D systems which does not belong to the clarified categories. As one of the main results, a constructive realization procedure is first proposed. Based on the proposed procedure, sufficient conditions and explicit construction for minimal realizations of the considered 2D systems are shown. In addition, possible variations and applications of the obtained results are discussed and illustrative examples are presented.
In English learning, speaking practice is crucial, but traditional classroom teaching can hardly meet the needs of most learners. In this paper, we investigate and improve the two essential techniques of pronunciation...
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In general, mechanical designers have to manually select assembly tolerance types and values in product design. To reduce the uncertainty in manufacturing process, solve the problem of effectively sharing and smoothly...
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ISBN:
(纸本)9781467371902
In general, mechanical designers have to manually select assembly tolerance types and values in product design. To reduce the uncertainty in manufacturing process, solve the problem of effectively sharing and smoothly exchange tolerance information among heterogeneous CAD system. On the optimization of tolerance synthesis with an ontology-based approach is proposed, automatically generated the tolerance type, variations of tolerance, cost function and tolerance value. Firstly, ontology contains abundant semantic knowledge and semantic structure. Secondly, the Web Ontology Language (OWL) is used to define the concepts of tolerance synthesis, and Semantic Web Rule Language (SWRL) is used to define the constraint conditions and distribute experience. Thirdly, based on the genetic algorithm, a tolerance values optimization model is established with manufacturing cost functions and assembly stack-up constraint. Finally, the effectiveness of the proposed approach is illustrated by using a practical example of the gear case.
The data acquisition of 3D-Ultrasound includes array scan and mechanical scan, and the later one is more easy to realize. Currently, the traditional probe scanning mode is Front-end scanning. Under the above scanning ...
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作者:
纪建田铮Department of Computer Science & Technology
Northwestern Polytechnical University Xi'an 710072 Department of Applied Mathematics
Northwestern Polytechnical UniversityXi'an 710072 Key Laboratory of Education Ministry for Image Processing and Intelligent ControlHuazhong University of Science & TechnologyWuhan 430074
The separation of noisy image is a very exciting area of research, especially when no prior information is available about the noisy image. In this paper, we propose a robust independent component analysis (ICA) net...
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The separation of noisy image is a very exciting area of research, especially when no prior information is available about the noisy image. In this paper, we propose a robust independent component analysis (ICA) network for separation images contaminated with high-level additive noise or outliers. We reduce the power of additive noise by adding outlier rejection rule in ICA. Extensive computer simulations confirm robustness and the excellent performance of the resulting algorithms.
Vehicle scheduling plays a profound role in public ***,stochastic vehicle scheduling may lead to more robust *** solve the stochastic vehicle scheduling problem(SVSP),a discrete artificial bee colony algorithm(DABC)is...
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Vehicle scheduling plays a profound role in public ***,stochastic vehicle scheduling may lead to more robust *** solve the stochastic vehicle scheduling problem(SVSP),a discrete artificial bee colony algorithm(DABC)is *** to the discreteness of SVSP,in DABC,a new encoding and decoding scheme with small dimensions is designed,whilst an initialization rule and three neighborhood search schemes(i.e.,discrete scheme,heuristic scheme,and learnable scheme)are devised individually.A series of experiments demonstrate that the proposed DABC with any neighborhood search scheme is able to produce better schedules than the benchmark results and DABC with the heuristic scheme performs the best among the three proposed search schemes.
Searching interesting regions in aerial video is a new and challenging problem. This paper presents an approach to detect visual interesting regions in aerial video using pLSA topic model. Traditional interesting regi...
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ISBN:
(纸本)9781457701221
Searching interesting regions in aerial video is a new and challenging problem. This paper presents an approach to detect visual interesting regions in aerial video using pLSA topic model. Traditional interesting region detection approaches just use bottom-up information, such as color, orientation and movement etc. Our proposed method can discover the semantic content of the whole image, the co-occurrence of local image patches via pLSA model, and consequently improve detection result significantly in real world scenes. First, we extract frames from aerial video as documents. Then we use vector quantized SIFT descriptors as words. Third, we discover topics (e.g. plants, roads, buildings) and the relation among them using pLSA model. Finally, we can detect interesting regions as we need according to calculated models. Experimental observations show the success of our approach on interesting region detection in aerial video.
Head pose plays an important role in Human- Computer interaction, and its estimation is a challenge problem compared to face detection and recognition in computer vision. In this paper, a novel and efficient method is...
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Head pose plays an important role in Human- Computer interaction, and its estimation is a challenge problem compared to face detection and recognition in computer vision. In this paper, a novel and efficient method is proposed to estimate head pose in real-time video sequences. A saliency model based segmentation method is used not only to extract feature points of face, but also to update and rectify the location of feature points when missing happened. This step also gives a benchmark for vector generation in pose estimation. In subsequent frames feature points will be tracked by sparse optical flow method and head pose can be determined from vectors generated by feature points between successive frames. Via a voting scheme, these vectors with angle and length can give a robust estimation of the head pose. Compared with other methods, annotated training data set and training procedure is not essential in our method. Initialization and re-initialization can be done automatically and are robust for profile head pose. Experimental results show an efficient and robust estimation of the head pose.
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