The dropping off of data during information transmission and the storage device’s damage etc.often leads the sampled data to be non-uniform.The paper, based on the stability theory of irregular wavelet frame and the ...The dropping off of data during information transmission and the storage device’s damage etc.often leads the sampled data to be non-uniform.The paper, based on the stability theory of irregular wavelet frame and the irregular weighted wavelet frame operator,proposed an irregular weighted wavelet fame conjugate gradient iterative algorithm for the reconstruction of non-uniformly sampling signal. Compared the experiment results with the iterative algorithm of the Ref.[5],the new algorithm has remarkable advantages in approximation error,running time and so on.展开更多
Aiming at the problem of video key frame extraction, a density peak clustering algorithm is proposed, which uses the HSV histogram to transform high-dimensional abstract video image data into quantifiable low-dimensio...Aiming at the problem of video key frame extraction, a density peak clustering algorithm is proposed, which uses the HSV histogram to transform high-dimensional abstract video image data into quantifiable low-dimensional data, and reduces the computational complexity while capturing image features. On this basis, the density peak clustering algorithm is used to cluster these low-dimensional data and find the cluster centers. Combining the clustering results, the final key frames are obtained. A large number of key frame extraction experiments for different types of videos show that the algorithm can extract different number of key frames by combining video content, overcome the shortcoming of traditional key frame extraction algorithm which can only extract a fixed number of key frames, and the extracted key frames can represent the main content of video accurately.展开更多
In order toovercomethe poor local search ability of genetic algorithm, resulting in the basic genetic algorithm is time-consuming, and low search abilityin the late evolutionary, we use thegray coding instead ofbinary...In order toovercomethe poor local search ability of genetic algorithm, resulting in the basic genetic algorithm is time-consuming, and low search abilityin the late evolutionary, we use thegray coding instead ofbinary codingatthebeginning of the coding;we use multi-point crossoverto replace the originalsingle-point crossoveroperation.Finally, theexperimentshows that the improved genetic algorithmnot only has a strong search capability, but also thestability has been effectively improved.展开更多
In response to the complex and multidimensional nature of converged traffic on heterogeneous links in tactical communication networks,which leads to the difficulty in ensuring the quality of service(QoS)requirements f...In response to the complex and multidimensional nature of converged traffic on heterogeneous links in tactical communication networks,which leads to the difficulty in ensuring the quality of service(QoS)requirements for critical services,a frame generation algorithm for differentiated services(DS-FG)is proposed.DS-FG deploys an adaptive frame generation algorithm based on deep reinforcement learning(DRL-FG)for timesensitive service,while deploying a high efficient frame generation(HEFG)algorithm for non-time-sensitive service.DRL-FG constructs a reward function by combining the queue status information of time-sensitive service and utilizes deep deterministic policy gradients(DDPG)to train a decision model for adaptive frame generation(AFG)algorithm thresholds.Furthermore,Gaussian noise sampling and prioritized experience replay strategies are employed to enhance model training efficiency and performance,achieving optimal matching between time-sensitive service QoS requirements and frame generation thresholds.Experimental results demonstrate that DS-FG outperforms traditional algorithms,achieving up to 13%improvement in throughput and over 19.7%reduction in average queueing delay for time-sensitive service.展开更多
针对商用车车架制造商中纵梁以及总装的生产工艺的多样性和生产调度的复杂性,以最小化最大完工时间、物料积压程度和耗电量为优化目标,提出了一个NSGA-Ⅱ和红狐算法的混合算法(hybrid algorithm of non-dominant sorting genetic algori...针对商用车车架制造商中纵梁以及总装的生产工艺的多样性和生产调度的复杂性,以最小化最大完工时间、物料积压程度和耗电量为优化目标,提出了一个NSGA-Ⅱ和红狐算法的混合算法(hybrid algorithm of non-dominant sorting genetic algorithm and red fox algorithm,HNSGA2RFA),用于解决多目标的柔性流水车间调度问题。通过ROV规则实现GA和RFA的编码转换,并提出了归一化分组策略(normalized grouping strategy)。试验结果表明,HNSGA2RFA算法在优化速度和最优解集数量上均优于原NSGA-Ⅱ算法。展开更多
基金supported by Hunan Education Office Foundation under Grant 06C260
文摘The dropping off of data during information transmission and the storage device’s damage etc.often leads the sampled data to be non-uniform.The paper, based on the stability theory of irregular wavelet frame and the irregular weighted wavelet frame operator,proposed an irregular weighted wavelet fame conjugate gradient iterative algorithm for the reconstruction of non-uniformly sampling signal. Compared the experiment results with the iterative algorithm of the Ref.[5],the new algorithm has remarkable advantages in approximation error,running time and so on.
文摘Aiming at the problem of video key frame extraction, a density peak clustering algorithm is proposed, which uses the HSV histogram to transform high-dimensional abstract video image data into quantifiable low-dimensional data, and reduces the computational complexity while capturing image features. On this basis, the density peak clustering algorithm is used to cluster these low-dimensional data and find the cluster centers. Combining the clustering results, the final key frames are obtained. A large number of key frame extraction experiments for different types of videos show that the algorithm can extract different number of key frames by combining video content, overcome the shortcoming of traditional key frame extraction algorithm which can only extract a fixed number of key frames, and the extracted key frames can represent the main content of video accurately.
文摘In order toovercomethe poor local search ability of genetic algorithm, resulting in the basic genetic algorithm is time-consuming, and low search abilityin the late evolutionary, we use thegray coding instead ofbinary codingatthebeginning of the coding;we use multi-point crossoverto replace the originalsingle-point crossoveroperation.Finally, theexperimentshows that the improved genetic algorithmnot only has a strong search capability, but also thestability has been effectively improved.
基金supported by the National Natural Science Foundation of China under Grant 61931004the Key Laboratory of Intelligent Support Technology for Complex Environments,Ministry of Education under Grant B2202401.
文摘In response to the complex and multidimensional nature of converged traffic on heterogeneous links in tactical communication networks,which leads to the difficulty in ensuring the quality of service(QoS)requirements for critical services,a frame generation algorithm for differentiated services(DS-FG)is proposed.DS-FG deploys an adaptive frame generation algorithm based on deep reinforcement learning(DRL-FG)for timesensitive service,while deploying a high efficient frame generation(HEFG)algorithm for non-time-sensitive service.DRL-FG constructs a reward function by combining the queue status information of time-sensitive service and utilizes deep deterministic policy gradients(DDPG)to train a decision model for adaptive frame generation(AFG)algorithm thresholds.Furthermore,Gaussian noise sampling and prioritized experience replay strategies are employed to enhance model training efficiency and performance,achieving optimal matching between time-sensitive service QoS requirements and frame generation thresholds.Experimental results demonstrate that DS-FG outperforms traditional algorithms,achieving up to 13%improvement in throughput and over 19.7%reduction in average queueing delay for time-sensitive service.
文摘针对商用车车架制造商中纵梁以及总装的生产工艺的多样性和生产调度的复杂性,以最小化最大完工时间、物料积压程度和耗电量为优化目标,提出了一个NSGA-Ⅱ和红狐算法的混合算法(hybrid algorithm of non-dominant sorting genetic algorithm and red fox algorithm,HNSGA2RFA),用于解决多目标的柔性流水车间调度问题。通过ROV规则实现GA和RFA的编码转换,并提出了归一化分组策略(normalized grouping strategy)。试验结果表明,HNSGA2RFA算法在优化速度和最优解集数量上均优于原NSGA-Ⅱ算法。
