To solve the multi-objective conflict problem of independent task scheduling in grid computing, model the system along the direction of multi-objective gradient, give the model solution procedure, propose grid scheduling algorithm based on multi-objective non-conflict degree, that is, application of gradient ascent method does a quadratic optimization for the global optimal solution obtained by genetic algorithm, compensate for the GA (genetic algorithm) deficiency in the ability of local search. The experiments demonstrate that the proposed algorithm is better than other tasks scheduling algorithms simply using GA.
For the single channel autoregressive moving average (ARMA) signals with multisensor and a colored measurement noise, when the model parameters and noise variances are partially unknown, based on identification method and Gevers-Wouters algorithm with a dead band, a self-tuning weighted measurement fusion Kalman signal filter is presented. A simulation example applied to signal processing shows its effectiveness.
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