Nonlinear Correlation Coefficient (NCC) is proposed to quantitatively measure the nonlinear relation between the variables. Much attention paid on NCC leads to application being far from the basic research. In this pa...
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Nonlinear Correlation Coefficient (NCC) is proposed to quantitatively measure the nonlinear relation between the variables. Much attention paid on NCC leads to application being far from the basic research. In this paper, we propose a mathematical framework to systematically analyze the effects of statistical distribution on NCC. It is found that the arbitrary distortion on distribution leads to the decreasing of NCC and the sharing structure of the concerned distribution minimizes the NCC. Furthermore, considering the situation of a sequence of discrete observations, we provide a collection of rigorous logistic results to justify NCC is an increasing function of sequence length. The numerical examples on Lorenz and linear auto-regression system are used to illustrate proposed results suitably and effectively.
Modern technology offers the possibility to construct networked monitoring systems from autonomous computing nodes equipped with appropriate sensors. Complementing such a system with actuators yields a cyber-physical ...
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Modern technology offers the possibility to construct networked monitoring systems from autonomous computing nodes equipped with appropriate sensors. Complementing such a system with actuators yields a cyber-physical system that must be able to cope with uncertainties arising from feedback loops via the physical world. The common property of such systems lies in the high degree of uncertainty in the varying configuration of the system and also in the potentially high amounts of (unstructured) data that can be generated by such a system. In order to tackle these problems and make the distributed monitoring systems more usable the concepts of situational information and hierarchies of situations can be applied in this domain. The problem of high amounts of data can be partially solved by arriving at a higher level of abstraction lower in the processing chain, communicating only data fused into an ontological structure to information consumers. The fusion templates are called situation parameters and values of the fused data items are called situational parameter values in the context of the current article. Situation parameter values must be tagged with situational and temporal validity information in order to cope with the delays and spatial uncertainties that can occur in a distributed monitoring system. The lower level situation parameters can be fused to even higher level situation parameters, projecting the temporal and spatial validity information from the lower level parameters up to the higher level parameters. The article presents the concepts of forming situational information templates and hierarchies based on data available from a distributed monitoring system where the temporal and spatial properties of situational information are taken into account. A case study is presented that shows the feasibility of the concepts in a real world monitoring scenario.
Markov models are well established technique used widely for modeling equipment deterioration. This work presents an approach where Markov models represent equipment ageing and also incorporate various maintenance act...
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The chapter is focused on the human resource influence on dependability of discrete transportation systems (DTS). The human resource means the driver of the vehicle. We add him/her as a new element of the system descr...
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This paper presents a robust object tracking method using a sparse shape-based object model for embedded systems with limited computational capabilities. Our approach consists of three ingredients namely shapes, a mot...
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The chapter presents a method of Web-based information system dependability analysis based on functional and reliability approach. A service availability is predicted by developed by authors a two level simulator (usi...
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Abstract The paper considers stability of nonlinear discrete-time system linearized by output feedback. The boundedness of the control signal inside the linearized closed-loop system is studied in the research present...
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Abstract The paper considers stability of nonlinear discrete-time system linearized by output feedback. The boundedness of the control signal inside the linearized closed-loop system is studied in the research presented in this article. The algorithm for determination of the region of admissible inputs of the closed-loop system ensuring bounded-input bounded-output behavior of the controlled model is introduced. Both static and dynamic output feedback linearization algorithms are examined. To make the research more clear, the main results and applicability of the theory presented in the paper are demonstrated on several examples.
In this paper, a novel multi-modal optimization algorithm, namely Dcopt-aiNet is proposed, which is based on biological immune network mechanism for global numerical optimization. Different from de Castro's opt-ai...
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In this paper, a novel multi-modal optimization algorithm, namely Dcopt-aiNet is proposed, which is based on biological immune network mechanism for global numerical optimization. Different from de Castro's opt-aiNet algorithm, Dcopt-aiNet models cloning operation using dynamic cloning operation which is adopted from biological immune network mechanism. Based on the multi-modal benchmarks, experiments were carried out to compare the performance of Dcopt-aiNet with that of opt-aiNet. Experiment results show that when compared with the opt-aiNet method, the new algorithm is capable of improving search performance significantly in successful rate and convergence speed.
As the feature size of FPGA shrinks to nanometers, SRAM-based FPGAs are more vulnerable to soft errors. During logic synthesis, reliability of the design can be improved by introducing logic masking effect. In this wo...
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As the feature size of FPGA shrinks to nanometers, SRAM-based FPGAs are more vulnerable to soft errors. During logic synthesis, reliability of the design can be improved by introducing logic masking effect. In this work, we observe that there are a lot of not-fully occupied look-up tables (LUTs) after logic synthesis. Hence, we propose a functional equivalent class based soft error mitigation scheme to exploit free LUT entries in the circuit. The proposed technique replaces not fully-occupied LUTs with corresponding functional equivalent classes, which can improve the reliability while preserve the functionality of the design. Experimental results show that, compared with the baseline ABC mapper, the proposed technique can reduce the soft error rate by 21%, and the critical-path delay increase is only 4.25%.
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