Similarity matching is one of the most important operations for data mining over time series. But previous works mainly focus on certain data. With the development of the internet of things and sensor networks, uncert...
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The Dynamical Optimization Evolutionary Algorithms (DOEAs) have been applied to solve Dynamical Optimization Problems which are very common in real-world applications. But little work focused on the convergent DOEAs. ...
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In this paper we present a Bellman equation for computing robust regions of attraction for state-constrained perturbed discrete-time systems. The robust region of attraction of interest is a set of states such that ev...
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In this paper we present a Bellman equation for computing robust regions of attraction for state-constrained perturbed discrete-time systems. The robust region of attraction of interest is a set of states such that every trajectory initialized in it will approach an equilibrium while never violating a specified state constraint, regardless of the actual perturbation. In this approach, the interior of the maximal robust region of attraction is characterized as the strict one sub-level set of the unique bounded and continuous solution to a Bellman equation.
In this paper we propose a convex programming based method for computing robust regions of attraction for state-constrained perturbed discrete-time polynomial systems. The robust region of attraction of interest is a ...
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In this paper we propose a convex programming based method for computing robust regions of attraction for state-constrained perturbed discrete-time polynomial systems. The robust region of attraction of interest is a set of states such that every possible trajectory initialized in it will approach an equilibrium state while never violating the specified state constraint, regardless of the actual perturbation. Based on a Bellman equation which characterizes the interior of the maximal robust region of attraction as the strict one sub-level set of its unique bounded and continuous solution, we construct a semi-definite program for computing robust regions of attraction. Under appropriate assumptions, the existence of solutions to the constructed semi-definite program is guaranteed and there exists a sequence of solutions such that their strict one sub-level sets inner-approximate and converge to the interior of the maximal robust region of attraction in measure. Finally, we demonstrate the method by two examples.
The crosscutting phenomena has been found at architectural level. Using aspects, AOP effectively solves the code tangling problem produced by the crosscutting phenomena at code level. This paper presents an approach t...
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This paper presents a rasterization rendering pipeline namely FreePipe. The system builds a bridge between the traditional graphics pipelines and the general purpose computing architecture CUDA by taking advantages of...
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Secure group key distribution and efficient rekeying is one of the most challenging security issues in ad hoc networks at present. In this paper, Latin squares are used to construct orthogonal arrays in order to quick...
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ISBN:
(纸本)9781595937575
Secure group key distribution and efficient rekeying is one of the most challenging security issues in ad hoc networks at present. In this paper, Latin squares are used to construct orthogonal arrays in order to quickly obtain t-packing designs. Based on cover-free family properties, t-packing designs are adopted in key predistribution phase. Then the pre-deployed keys are used for implementing secure channels between members for group key distribution. The new scheme improves the collusion-resilience of the networks using the cover-free family properties, and enhances the key-sharing connectivity of nodes which makes key management more efficient. This paper also presents in depth theory and data analysis of the new scheme in terms of network security and connectivity.1 Copyright 2007 ACM.
Many practical applications are dynamic over time, which require optimization algorithms not only to converge to optimum as soon as possible but also to track the changing optimum. In this paper, a Cooperative Dual-sw...
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In this paper, a Kansei landscape image retrieval system named KIRCK is proposed, which is based on color feature and Kansei factors. Color feature is extracted in HSV color space and the similarity of color feature i...
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In this paper, a Kansei landscape image retrieval system named KIRCK is proposed, which is based on color feature and Kansei factors. Color feature is extracted in HSV color space and the similarity of color feature is estimated by color accumulation histogram intersection method. Multi-class Support Vector Machine is applied for the mapping between high-level Kansei lab.ls and low-level image characteristics. After the multi-class SVM is trained, Kansei factors of images can be lab.led automatically, and the similarity of images in Kansei space also can be estimated. Thus integrated retrieval results using color and Kansei factors can be obtained, and the experiment shows that these retrieval results are more satisfied than only using color feature or Kansei factors. Correlative feedback is also introduced to improve the performance of our color feature and Kansei factors image retrieval.
Character Modeling is becoming more and more difficult in animation industry today. Lots of designers are usually involved to cooperatively accomplish a character by computer networks or the Internet. This paper prese...
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