There are two important factors in the powerperformance issues of chip multi-processor (CMP) system: the execution time of tasks and the system energy consumption. Most of exist energy saving methods are not designed to reduce the system energy while cut the execution time down. This paper represents a multi-objective hybrid genetic algorithm (MHGA) which can make the execution time of tasks minimize while reducing the system power consumption. We analyze the problem of energy saving task scheduling on CMP system and a novel coding scheme of genetic algorithm. Based on that, we improve the crossover and mutation operator of genetic algorithm. We propose the multi-objective genetic algorithm by using simulated annealing algorithm to enhance the search ability. Simulation results demonstrate that using our algorithm can make the efficiency of task scheduling on CMP increase, make both the execution time of task and energy consumption of system decrease.Keywords-genetic algorithm, chip multi-processor (CMP), energy saving task scheduling I.
Focus on the estimation for DOA and polarization parameters of electromagnetic sensor array, this paper proposes the method that uses cyclic relation function to substitute for covariance matrix. Because cyclic statistic is less sensitive to stable noise and any cyclic stable noise with different cyclic frequency, the method proposed is immune to any stable color noise. This method use minimum norm method to solve the spectrum function. So this method can restrict the effect of the cyclic relation matrix estimating error. Computer simulation experiments prove the performance of this method.
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