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Task scheduling is one key issue in computational overlay grid. For finding solution to this problem, we propose a Chaotic Neural Network Algorithm for Task Scheduling, the goal of this algorithm is to minimize the total execution time of task by appropriately mapping the task to processor in the parallel system. We formulate the task scheduling problem that considers heterogeneousness. To evaluate...
A hierarchical semantic perceptron grid architecture based neural network has been proposed in this paper, the semantic spotting is a key issue of this architecture, for finding solution to this problem, firstly we has formulated it, then a semantic neural network classifier frame has been proposed. And experiment results of this scenario were presented, to evaluate the effectiveness of this scenario,...
A first-order signal derivative estimator via bang-bang switching is presented in this paper. The derivative estimator can be used as a direct derivative estimation of smooth and bounded input signals. Digital implementation shows the effectiveness of the derivative estimator. High-order signal differentiation can be obtained by concatenating a set of the proposed first-order derivative estimators...
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