This paper is concerned with the problems of quantized *** for discrete-time Markovian jump linear systems over networks with non-accessible mode information. The quantizer considered here is logarithmic quantizer. In...
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This paper is concerned with the problems of quantized *** for discrete-time Markovian jump linear systems over networks with non-accessible mode information. The quantizer considered here is logarithmic quantizer. In this paper, a linear time-invariant mode-independent quantized *** is designed such *** error system is stochastically stable. *** conditions for the existence of *** is given in terms of linear matrix inequalities. A numerical example is provided to demonstrate the effectiveness of the proposed approach.
Grid is a promising infrastructure which enables scientists and engineers to access geographically distributed resources. Grid computing is a new technology which focuses on aggregating various kinds of resource (e.g....
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ISBN:
(纸本)9781424476169
Grid is a promising infrastructure which enables scientists and engineers to access geographically distributed resources. Grid computing is a new technology which focuses on aggregating various kinds of resource (e.g., processor cycles, disk storage, and contents) into one computing platform. The realization of grid computing requires a resource agent to manage and monitor available resources. Based on study of past models, this paper presents a new agent-based resource monitoring model whose main feature is multi-layered monitoring architecture, which enhances the ability to monitor related resource efficiently. In the meantime, the new model has been implemented in the development of a resource monitoring module integrated within a academic grid project.
Interaction testing has addressed some issues on how to select a small subset of test cases. In many systems where interaction testing is needed, the entire test suite is not executed because of time or budget constra...
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ISBN:
(纸本)9781424463886;9780769539874
Interaction testing has addressed some issues on how to select a small subset of test cases. In many systems where interaction testing is needed, the entire test suite is not executed because of time or budget constraints. It is important to prioritize the test cases in these situations. On the other hand, there are not always interactions among any factors in real systems. Moreover, some factors may need N-way (N>2) testing since there is a closer relationship among them. We present a model for prioritized interaction testing with interaction relationship and propose a greedy algorithm for generating variable strength covering arrays with bias.
Facing changing environments and evolving business, service composition happens all time. However, services do not always interact properly because of mismatches between their interfaces. In this paper, we use labelle...
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Facing changing environments and evolving business, service composition happens all time. However, services do not always interact properly because of mismatches between their interfaces. In this paper, we use labelled interface automata, an extension of interface automata, to illustrate mismatching interfaces and resolution approaches. We model service interfaces with labelled interface automata and propose a theorem for mismatch detecting. Then we characterize mismatches between pairs of interfaces by identifying and classifying them into six basic scenarios, and illustrate the resolution approach of mismatches. Our method formalizes the interface adaptation problem and provides convenience to detect mismatches and build adaptors for service interactions.
This paper presents a hierarchical feature extraction and classification method for electroencephalogram (EEG) hidden information mining. It consists of supervised learning for fewer features, hierarchical knowledge b...
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This paper presents a hierarchical feature extraction and classification method for electroencephalogram (EEG) hidden information mining. It consists of supervised learning for fewer features, hierarchical knowledge base (HKB) construction and classification test. First, the discriminative rules and the corresponding background conditions are extracted by using autoregressive method in combination with the nonparametric weighted feature extraction (NWFE) and k-nearest neighbor. Second, through ranking the discriminative rules according to validation test correct rate, a hierarchical knowledge base HKB is constructed. Third, given an EEG sequence, it chooses one or several discriminative rules from the HKB using the up-bottom search strategy and calculates classification accuracy. The experiments are carried out upon real electroencephalogram (EEG) recordings from five subjects and the results show the better performance of our method.
Passive sensor networks can achieve accurate detection of target under complex environment In order to adapt to different communication demands of sensor networks in different environments, this paper designed and...
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ISBN:
(纸本)9781424479573
Passive sensor networks can achieve accurate detection of target under complex environment In order to adapt to different communication demands of sensor networks in different environments, this paper designed and implemented a wireless and wired mixed communication module, that is, a communication system combined short-distance wireless communication based on radio frequency technology with broadband cable communication. Simulation results show that our system can achieve the desired requirements in different circumstances.
Lots of rear end collisions due to driver inattention have been identified as a major automotive safety issue. A short advance warning can reduce the number and severity of the rear end collisions. This paper describe...
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Lots of rear end collisions due to driver inattention have been identified as a major automotive safety issue. A short advance warning can reduce the number and severity of the rear end collisions. This paper describes a Forward Collision Warning (FCW) system based on monocular vision, and presents a new vehicle detection method: appearance-based hypothesis generation, template tracking-based hypothesis verification which can remove false positive detections and automatic image matting for detection refinement. The FCW system uses time to collision (TTC) to trigger the *** order to compute time to collision (TTC), firstly, haar and adaboost algorithm is utilized to detect the vehicle; Secondly, we use simplified Lucas-Kanade algorithm and virtual edge to remove false positive detection and use automatic image matting to do detection refinement; Thirdly, hierarchical tracking system is introduced for vehicle tracking; Camera calibration is utilized to get the headway distance and TTC at last. The use of a single low cost camera results in an affordable system which is simple to install. The FCW system has been tested in outdoor environment, showing robust and accurate performance.
We study the capacity scaling laws for the cognitive network that consists of the primary hybrid network (PhN) and secondary ad hoc network (SaN). PhN is further comprised of an ad hoc network and a base station based...
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Knowledge reduction, one of essential issues for data mining, has alwaysbeen a, hot topic due to the explosive growth of inform,a,tion. However, whenhandling large-scale data, m,any current knowledge reduction m,ethod...
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Continuing growth and increasing complexity of distributed software systems make them be more flexible, adaptive and easily extensible. Dynamic evolution or reconfiguration of distributed software systems is one possi...
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