In the last decade, moving horizon estimation (MHE) has emerged as a powerful technique for tackling the problem of estimating the state of a dynamic system in the presence of nonlinearities and disturbances. MHE is b...
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ISBN:
(纸本)9781424477456
In the last decade, moving horizon estimation (MHE) has emerged as a powerful technique for tackling the problem of estimating the state of a dynamic system in the presence of nonlinearities and disturbances. MHE is based on the idea of minimizing an estimation cost function defined on a sliding window composed of a finite number of time stages. The cost function is usually made up of two contributions: a prediction error computed on a recent batch of inputs and outputs;an arrival cost that serves the purpose of summarizing the past data. However, the diffusion of such techniques has been hampered by: i) the difficulty in choosing the arrival cost so as to ensure stability of the overall estimation scheme;ii) the request of an adequate computational effort on line. In this paper, both problems are addressed and possible solutions are proposed. First, by means of a novel stability analysis, it is constructively shown that under very general observability conditions a quadratic arrival cost is sufficient to ensure the stability of the estimation error provided that the weight matrix is adequately chosen. Second, a novel approximate MHE algorithm is proposed that is based on nonlinear programming sensitivity calculations. The approximate MHE algorithm has the same stability properties of the optimal one which make the overall approach suitable to be applied in real settings. Preliminary simulation results confirm the effectiveness of proposed method.
Mean-variance relationship (MVR), nowadays agreed in power law form, is an important function. It is currently used by traffic matrix estimation as a basic statistical assumption. Because all the existing papers obt...
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Mean-variance relationship (MVR), nowadays agreed in power law form, is an important function. It is currently used by traffic matrix estimation as a basic statistical assumption. Because all the existing papers obtain MVR only through empirical ways, they cannot provide theoretical support to power law MVR or the definition of its power exponent. Furthermore, because of the lack of theoretical model, all traffic matrix estimation methods based on MVR have not been theoretically supported yet. By observing both our laboratory and campus network for more than one year, we find that such an empirical MVR is not sufficient to describe actual network traffic. In this paper, we derive a theoretical MVR from ON/OFF model. Then we prove that current empirical power law MVR is generally reasonable by the fact that it is an approximate form of theoretical MVR under specific precondition, which can theoretically support those traffic matrix estimation algorithms of using MVR. Through verifying our MVR by actual observation and public DECPKT traces, we verify that our theoretical MVR is valid and more capable of describing actual network traffic than power law MVR.
This paper describes gait identification using cumulants of accelerometer data. Accelerometer data of three different walking speeds for each subject (normal, slow and fast) was acquired by a cell phone placed on the ...
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ISBN:
(纸本)9789604741359
This paper describes gait identification using cumulants of accelerometer data. Accelerometer data of three different walking speeds for each subject (normal, slow and fast) was acquired by a cell phone placed on the person's hip. Data analysis was based on gait cycles that were detected first. Cumulants of order from 1 to 4 with lags from 0 to 10 for second, third and fourth order cumulants were calculated from the cycles and used as feature vectors for classification which was accomplished by support vector machines (SVM). Six healthy young subjects participated in the experiment. According to their gait classification the average recognition rate was 93.1%. A similarity measure for discerning different walking types of the same subject was also introduced using principal component analysis (PCA).
This paper presents a novel method to implement an interactive mobile robot. The proposed mobile robot is implemented under the technique of mixed reality. The mixed reality technique is realized by both the Virtools ...
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This paper is mainly concerned with the study of the PBG (Photonic Band Gap) in 2D photonic crystal which consists of a hexagonal lattice of circular dielectric rods with Polyethylene. The result indicates that its PB...
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Traditional commercial instruments utilized in vision screening programs cannot satisfy the request for real-time diopter measurement by far, and their success is limited by some defectiveness such as computer-attache...
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In multicore environment, using multiple threads is a common useful approach to improve application performance. Nevertheless, even in many simple applications, the performance might degrade when the number of threads...
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In this paper, we propose a new patch-based texture synthesis method. The core of the proposed method consists of two main components: (1) a feature-weighted similarity measurement to search for the best match and (2)...
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In this paper, we propose a new patch-based texture synthesis method. The core of the proposed method consists of two main components: (1) a feature-weighted similarity measurement to search for the best match and (2) a dynamically prioritized-based pixel re-synthesis to reduce discontinuity at the boundary of adjacent patches. Examples and experimental comparisons with other previous methods are demonstrated to verify the usefulness of our proposed method. In addition, we enhance the proposed method with a view warping technique to better synthesize non-frontal-parallel textures (NFPTs) that can not be synthesized well by traditional texture synthesis methods.
Efficient rendering of complex scenes has receive great attention in real-time computer graphics. Current researches are mostly concentrated on reducing the geometric complexity of the scene model such as reconstructi...
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Efficient rendering of complex scenes has receive great attention in real-time computer graphics. Current researches are mostly concentrated on reducing the geometric complexity of the scene model such as reconstructing an LOD representation, performing visibility culling etc. However, the rendering process of complex scenes involves not only the geometric information of each object, but also multiple attributes, including lighting, material, texture, etc. The invocation of each attribute corresponds to a specific state in the rendering pipeline, frequent transfer between different states in the pipeline will introduce large amount of overhead, hence reducing the rendering efficiency. A rendering method accounting for efficient invocation of multiple attributes of objects based on state transition optimization strategies is presented. It estimates the cost for invoking each attribute of objects in the rendering pipeline and expresses the transitions between various render states as a weighted directed graph. Then the optimized sequence of state transition is obtained by optimization. Experimental results show that our proposed method can effectively reduce the overhead of state transition and improve the rendering efficiency of scenes containing large amounts of multi-attribute objects.
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