Biologically adaptive robust mean shift algorithm with Cauchy predator-prey BBO and space variant resolution for unmanned helicopter formation

Visual tracking technology can provide measurement information for unmanned helicopter formation and thus, more attention is being paid to this research area. We propose a novel mean shift （MS） algorithm that is both adaptive and robust for unmanned helicopter formation and apply it to the leading unmanned helicopter tracking. The movement of an unmanned helicopter is very flexible and changeable, which makes the tracking there of more difficulty than for common targets. In creating an algorithm that can adapt to the acceleration of the unmanned helicopter and estimates both the scale and orientation of the movement changes, we combine the traditional MS with the bio-inspired Cauchy predator-prey biogeography-based optimization （CPPBBO） evolutionary algorithm, and also the space variant resolution （SVR） mechanism of the human visual system （MS-CPPBBO-SVR）. To demonstrate the effectiveness and robustness of the proposed method and justify the importance of the CPPBBO algorithm and SVR mechanism at the same time, a series of comparative exper- iments were carried out. The experimental results of the proposed MS-CPPBBO-SVR method are compared with other competitive tracking methods, such as MS, MS with SVR （MS-SVR）, MS-SVR with several other optimization algorithms, and the robust particle filter algorithm. The experimental results demonstrate that our proposed tracking approach, MS-CPPBBO-SVR, is more adaptive, robust and efficient in target tracking than the other methods.     

Decentralized transceiver optimization for multi-relay aided multiuser MIMO networks

In this paper, the decentralized transceivers and corresponding channel state information （CSI） signaling concepts are proposed for weighted sum rate （WSR） maximization, via linear downlink transceiver＂ optimization in multi-relay aided multiuser multiple-input multiple-output （MIMO） networks. Three decentral- ized algorithms are proposed with the local CSI requirements at the base station （BS） and the relay nodes. In the first proposed algorithm, the generalized channel inversion precoding is used at the BS to avoid the second hop channel sharing requirements among the relay nodes, and decentralized transceiver optimization of the relay nodes and users are developed to maximize the WSR. A minimum mean square error （MMSE）-based enhanced method is proposed as well. To further improve the performance, we provide a novel structure of the precoding matrix of the BS. The decentralized joint BS, relay and user transceiver optimization problem is formulated and solved. Also, the CSI signaling and decentralized processing in the time division duplex （TDD） system are analyzed. Simulation results show the effectiveness of the decentralized transceiver design compared to the existing algorithms.     

MABP: an optimal resource allocation approach in data center networks

In data center networks, resource allocation based on workload is an effective way to allocate the infrastructure resources to diverse cloud applications and satisfy the quality of service for the users, which refers to mapping a large number of workloads provided by cloud users/tenants to substrate network provided by cloud providers. Although the existing heuristic approaches are able to find a feasible solution, the quality of the solution is not guaranteed. Concerning this issue, based on the minimum mapping cost, this paper solves the resource allocation problem by modeling it as a distributed constraint optimization problem. Then an efficient approach is proposed to solve the resource allocation problem, aiming to find a feasible solution and ensuring the optimality of the solution. Finally, theoretical analysis and extensive experiments have demonstrated the effectiveness and efficiency of our proposed approach.     

Optimal resource allocation for transmission diversity in multi-radio access networks： a coevolutionary genetic algorithm approach

The next generation wireless communication systems aim at supporting enhanced diversified network access and data transmission abilities via the cooperative integration and unified management of various radio access technologies(RATs).The resource allocation is the core component leading the network system and mobile terminals to the service robustness and performance maximization.In this paper,a numeric optimization model for optimizing terminals’transmission power and allocated RAT bandwidth for maximizing system capacity is proposed with the focal consideration of the multi-radio transmission diversity for parallel transmission through multiple links from diferent RATs,and diferent terminal characteristics on RAT supports.Also,we design a centralized and periodic scheduling algorithm including an improved coevolutionary genetic algorithm for efciently solving the optimization problem.Simulation results demonstrate that our propose algorithm can distinctly enhance the system performance and improve the computational efciency.     

Oracle数据库系统优化调整

在过去的几十年中,Oracle数据库已经逐渐成为世界上最为广泛的大型数据库管理系统。而数据库DBA的重要工作就是要确保利用Oracle的强大特性来提高企业的生产力。其中最有效的方法就是通过Oracle调优,它有大量的调整参数和技术来改进Oracle数据库的性能。文章从数据库内存参数调整、索引技术、数据库分区以及SQL语句的优化等四个方面来研究Oracle数据库的性能调整。     

风机冷风保安控制系统优化

介绍菜钢型钢AV80风机冷风保安控制系统的优化改造,以增加其控制安全性及可靠性.     

Variable partial-update NLMS algorithms with data-selective updating

We note that some existing algorithms are based on the normalized least-mean square （NLMS） algorithm and aim to reduce the computational complexity of NLMS all inherited from the solution of the same optimization problem, but with different constraints. A new constraint is analyzed to substitute an extra searching technique in the set-membership partial-update NLMS algorithm （SM-PU-NLMS） which aims to get a variable number of updating coefficients for a further reduction of computational complexity. We get a closed form expression of the new constraint without extra searching technique to generate a novel set-membership variable-partial-update NLMS （SM-VPU-NLMS） algorithm. Note that tile SM-VPU-NLMS algorithm obtains a faster convergence and a smaller mean-squared error （MSE） than the existing SM-PU-NLMS. It is pointed out that the closed form expression can also be applied to the conventional variable-step-size partial-update NLMS （VSS-PU-NLMS） algorithm. The novel variable-step-size variable-partial-update NLMS （VSS-VPU-NLMS） algorithm is also verified to get a further computational complexity reduction. Simulation results verify that our analysis is reasonable and effective.     

Joint optimal sensing time and power allocation for multi-channel cognitive radio networks considering sensing-channel selection

In this paper,we consider a multi-channel cognitive radio network(CRN)where each secondary user(SU)can only choose to sense a subset of channels.We formulate a joint optimization problem of sensingchannel selection,sensing time and power allocation under the constraints of average transmit power budget and average interference power budget,which maximizes the CRN’s total throughput.We propose a greedy algorithm to solve the joint optimization problem,which has much less computational complexity.Moreover,it is shown that the search space of the greedy algorithm can be further pruned.Finally,numerical results demonstrate that the greedy algorithm has comparable performance to the exhaustive search algorithm.     

干熄焦提升机控制系统的优化

从控制时序、系统拓扑结构、传动部分等方面介绍干熄焦提升控制系统。通过一起焦罐坠落事故,分析干熄焦提升控制系统存在的问题,并提出解决方案。     

CDMA掉话高效优化工具研究与设计

随着现代通信技术的发展,无线通信技术已经在移动通信过程中得到了广泛的应用,发展到了3/4G时代。掉话一直是困扰无线通信技术发展的瓶颈,其由于覆盖、前反向不平衡、参数、终端及用户行为等无线通信固有的原因和特点,成为无线通信过程中需要长期实施优化解决的问题之一,得到了许多网优工作者的研究。