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为提升MIMO雷达发射功率利用率,改善对目标的探测性能,研究了期望方向图匹配下的发射波形设计方法。建立了发射波形恒模约束下的方向图匹配加权优化模型;基于循环优化和majorization-minimization(MM)算法对原始非凸优化问题进行求解,通过构造合适的上界函数,可将原始问题松弛为等式约束下的序列线性规划问题,并能保证算法的收敛性;由于每一次迭代都能给出子问题的闭式解,因而所提方法的计算复杂度较低;仿真实验表明了所提方法的有效性。 相似文献
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As the traditional semiconductor complementary metal oxide semiconductor (CMOS) integrated circuit technology gradually approaches the limit of Moore's Law, quantum computing, as a new system computing technology,with the potential for higher computing speed and lower power consumption, is getting more and more attention from governments and research institutions around the world. For instance, the United States (US) government is adopting a bunch of bills to deploy new quantum information processing technology. The European Union's “quantum declaration" plans to realize customized quantum computers with more than 100 qubits in the next 10 years. The Chinese government also provides strong support for quantum computer research through the project of National Science and Technology Major Projects. In the business field, major companies such as International Business Machines (IBM) Corporation, Intel, Google, Alibaba, Huawei, Baidu, etc. , have joined the “quantum supremacy" competition in order to seize the initiative in the future information field. Facing the rapid development trend of quantum computing, we believe that we should refer to the classical computer industry in the early stage, form an industrial system, and develop the quantum computing industry. We should also use the scientific system engineering method to carry out the research and development of the quantum computer and establish the ecological environment of the quantum computer industry with the demand as the traction, so as to better serve the development of the national economy. 相似文献
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Wang Yong Wei Xian Tang Xuan Wu Jingjing Fang Jiangxiong 《Neural computing & applications》2022,34(7):5757-5769
Neural Computing and Applications - In recent years, RGB and thermal sensors are widely used. There is complementary information from these two types of sensors. A fundamental task which arises in... 相似文献
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Link prediction has attracted wide attention among interdisciplinary researchers as an important issue in complex network. It aims to predict the missing links in current networks and new links that will appear in future networks. Despite the presence of missing links in the target network of link prediction studies, the network it processes remains macroscopically as a large connected graph. However, the complexity of the real world makes the complex networks abstracted from real systems often contain many isolated nodes. This phenomenon leads to existing link prediction methods not to efficiently implement the prediction of missing edges on isolated nodes. Therefore, the cold-start link prediction is favored as one of the most valuable subproblems of traditional link prediction. However, due to the loss of many links in the observation network, the topological information available for completing the link prediction task is extremely scarce. This presents a severe challenge for the study of cold-start link prediction. Therefore, how to mine and fuse more available non-topological information from observed network becomes the key point to solve the problem of cold-start link prediction. In this paper, we propose a framework for solving the cold-start link prediction problem, a joint-weighted symmetric nonnegative matrix factorization model fusing graph regularization information, based on low-rank approximation algorithms in the field of machine learning. First, the nonlinear features in high-dimensional space of node attributes are captured by the designed graph regularization term. Second, using a weighted matrix, we associate the attribute similarity and first order structure information of nodes and constrain each other. Finally, a unified framework for implementing cold-start link prediction is constructed by using a symmetric nonnegative matrix factorization model to integrate the multiple information extracted together. Extensive experimental validation on five real networks with attributes shows that the proposed model has very good predictive performance when predicting missing edges of isolated nodes. 相似文献
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Clustering divides objects into groups based on similarity. However, traditional clustering approaches are plagued by their difficulty in dealing with data with complex structure and high dimensionality, as well as their inability in solving multi-objective data clustering problems. To address these issues, an evolutionary state-based novel multi-objective periodic bacterial foraging optimization algorithm (ES-NMPBFO) is proposed in this article. The algorithm is designed to alleviate the high-computing complexity of the standard bacterial foraging optimization (BFO) algorithm by introducing periodic BFO. Moreover, two learning strategies, global best individual (gbest) and personal historical best individual (pbest), are used in the chemotaxis operation to enhance the convergence speed and guide the bacteria to the optimum position. Two elimination-dispersal operations are also proposed to prevent falling into local optima and improve the diversity of solutions. The proposed algorithm is compared with five other algorithms on six validity indexes in two data clustering cases comprising nine general benchmark datasets and four credit risk assessment datasets. The experimental results suggest that the proposed algorithm significantly outperforms the competing approaches. To further examine the effectiveness of the proposed strategies, two variants of ES-NMPBFO were designed, and all three forms of ES-NMPBFO were tested. The experimental results show that all of the proposed strategies are conducive to the improvement of solution quality, diversity and convergence. 相似文献
958.
RS(Reed-Solomon)码可以根据应用环境构造出任意容错能力的码字,有很好的灵活性,且使用RS纠删码作为容错方法的存储系统能达到理论最优的存储效率.但是,与异或(exclusive-OR,XOR)类纠删码相比,RS类纠删码译码计算的时间开销过大,这又很大程度上阻碍了它在分布式存储系统中的使用.针对这一问题,提出了一类RS纠删码的译码方法,该方法完全抛弃了当前大多RS类纠删码译码方法中普遍使用的矩阵求逆运算,仅使用计算复杂度更小的加法和乘法,通过构造译码变换矩阵并在此矩阵上执行相应的简单的矩阵变换,能够直接得出失效码元由有效码元组成的线性组合关系,从而降低译码计算复杂度.最后,通过理论证明了该方法的正确性,并且针对每种不同大小的文件,进行3种不同大小文件块的划分,将划分得到的数据块进行实验,实验结果表明:在不同的文件分块大小情况下,该新译码方法较其他方法的译码时间开销更低. 相似文献
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