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The general process of human's solving complex problem and the incompleteness of qualitative knowledge and quantitative knowledge when being used in solving complex problem are analyzed. Then a meta-synthesis approach and its framework to model the complex problem solving are put forward. According to this approach, the modeling process is divided into three phrases, which are the construction of...
Data grid integrates geographically distributed resources for solving data-sensitive scientific applications. As tasks are sensitive to data, dealing with large amount of data makes the requirement for efficiency in data access more critical. The goal of replica placement is to shorten data access time for enhancing the task execution performance. Therefore, replica placement strategies are often...
The stochastic gradient (SG) identification algorithm has a poor convergence rate. We extend the SG algorithm from the viewpoint of innovation modification and present multi-innovation stochastic gradient (MISG) identification algorithms. Since the multi-innovation stochastic gradient algorithms use not only the current data but also the past data at each iteration, parameter estimation accuracy can...
In this paper, a novel sequential noise estimation algorithm is proposed based on the 1st-order vector Taylor series (VTS) approximation to the nonlinear environmental function. The estimation formulas are derived in the sequential expectation-maximum (EM) criterion. Noise parameters, both the mean vectors and the covariance matrices, are estimated frame by frame directly with the aim to maximize...
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