Sensor registration is a basis for well-organized sensor network, and a precondition for data fusion. In cases of constant registration errors, batch processing methods are always applied, where the registration is ac...
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Sensor registration is a basis for well-organized sensor network, and a precondition for data fusion. In cases of constant registration errors, batch processing methods are always applied, where the registration is actually viewed as an optimization problem. Such methods are fast convergent, but sometimes they are not flexible in different cases and the optimal techniques used in batch processing methods may provide the suboptimum as solution. What's more, when dealing with a large number of sensors, the batch processing methods may come across numeric problems. To address the registration problem in some practical cases, the evolutionary algorithm based method can be explored. A method based on genetic algorithm, as well as the least squares method, are developed for sensor registration in different simulation scenarios and compared. Simulation results are analyzed to make clear the advantages and disadvantages of the methods.
In this paper, based on 3d wavelet moments we present a new method called fractal scale descriptors for 3d objects. Just like wavelet moments, they are still robust to translation, rotation and scale, and have the mul...
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In this paper, based on 3d wavelet moments we present a new method called fractal scale descriptors for 3d objects. Just like wavelet moments, they are still robust to translation, rotation and scale, and have the multi-resolution features in the radial direction, which can handle noise to some extent and provide multi-level features to satisfy various requirements. Furthermore the new method is prior to the original 3d wavelet moments in computational complexity by using the fast algorithm of the spherical harmonics together with the Mallat algorithm of the wavelets.
In this paper, an uncalibrated dynamic visual servoing algorithm is proposed and analyzed. No calibration or robot model is needed. After a brief introduction of the development of uncalibrated visual servoing, the th...
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In this paper, an uncalibrated dynamic visual servoing algorithm is proposed and analyzed. No calibration or robot model is needed. After a brief introduction of the development of uncalibrated visual servoing, the theoretical backgrounds and mathematical requirements of recursive least square (RLS) are stated respectively. Then the core uncalibrated visual servoing algorithm, in RLS form, or more technically, VS-RLS as well as its performance analysis, is investigated. After that, the experimental 6DOF Puma560 simulation of static and moving target tracking is demonstrated. Finally the weak and strength of the algorithm as well as the potential and promising improvements are discussed.
This paper presents a comprehensive overview of the current state of research in the area of Networked control systems (NCSs) first. Then two modeling and control methods are introduced for NCSs in details. The first ...
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This paper presents a comprehensive overview of the current state of research in the area of Networked control systems (NCSs) first. Then two modeling and control methods are introduced for NCSs in details. The first one is a stochastic control method, which investigates the H{sub}∞ control problem for NCSs with random network-induced delay. The second one is a switch control method, which focuses on solving the stabilization problem for NCSs in discrete-time domain, where both network-induced delay and packet dropout are taken into account. Illustrative examples are given to demonstrate the effectiveness of the proposed approaches. Finally, this paper concludes with the discussion of possible future development of NCSs from a control perspective.
Quantum information theory is a new interdisciplinary research field related to quantum mechanics, computer science, information theory, and applied mathematics. It provides completely new paradigms to do information ...
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Quantum information theory is a new interdisciplinary research field related to quantum mechanics, computer science, information theory, and applied mathematics. It provides completely new paradigms to do information processing tasks by employing the principles of quantum mechanics. In this review, we first survey some of the significant advances in quantum information theory in the last twenty years. We then focus mainly on two special subjects： discrimination of quantum objects and transformations between entanglements. More specifically, we first discuss discrimination of quantum states and quantum apparatus in both global and local settings. Secondly, we present systematical characterizations and equivalence relations of several interesting entanglement transformation phenomena, namely entanglement catalysis, multiple-copy entanglement transformation, and partial entanglement recovery.
In this paper, a visual similarity based document layout analysis （DLA） scheme is proposed, which by using clustering strategy can adaptively deal with documents in different languages, with different layout structu...
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In this paper, a visual similarity based document layout analysis （DLA） scheme is proposed, which by using clustering strategy can adaptively deal with documents in different languages, with different layout structures and skew angles. Aiming at a robust and adaptive DLA approach, the authors first manage to find a set of representative filters and statistics to characterize typical texture patterns in document images, which is through a visual similarity testing process. Texture features are then extracted from these filters and passed into a dynamic clustering procedure, which is called visual similarity clustering. Finally, text contents are located from the clustered results. Benefit from this scheme, the algorithm demonstrates strong robustness and adaptability in a wide variety of documents, which previous traditional DLA approaches do not possess.
The contrast function remains to be an open problem in blind source separation （BSS） when the number of source signals is unknown and/or dynamically changed. The paper studies this problem and proves that the mutual...
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The contrast function remains to be an open problem in blind source separation （BSS） when the number of source signals is unknown and/or dynamically changed. The paper studies this problem and proves that the mutual information is still the contrast function for BSS if the mixing matrix is of full column rank. The mutual information reaches its minimum at the separation points, where the random outputs of the BSS system are the scaled and permuted source signals, while the others are zero outputs. Using the property that the transpose of the mixing matrix and a matrix composed by m observed signals have the indentical null space with probability one, a practical method, which can detect the unknown number of source signals n, ulteriorly traces the dynamical change of the sources number with a few of data, is proposed. The effectiveness of the proposed theorey and the developed novel algorithm is verified by adaptive BSS simulations with unknown and dynamically changing number of source signals.
Since 1990s, a large amount of lane detection systems have been designed for comparatively simple road condition on highway. In this paper, we propose a real-time lane detection algorithm in some complex conditions, i...
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In this paper, a new approach to solve the inverse kinematics of a flexible macro-micro manipulator system is proposed. The macro-micro manipulator system consists of a macro flexible manipulator, and a micro rigid ma...
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