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几种约束广义逆矩阵的有限算法 总被引:2,自引:0,他引:2
陈永林 《高等学校计算数学学报》1997,19(3):232-240
1引言与引理众所周知,关于非奇异方阵的正则逆的有限算法是由Faddeev大给在1949年之前提出的,这就是著名的Faddeev算法[1,P…334-336]。自从五十年代中期广义逆矩阵的研究复兴与发展以来,有不少学者提出了关于广义逆矩阵的有限算法。第一个给出关于广义逆矩 相似文献
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在讨论MPT1327信令的集群移动通信系统与国内No.7信令的PSTN网间互连,帝现两种信令配合中,研究了集群系统的仿真模型和模拟算法,同时模拟出整个集群系统的工作情况,运行结果证实了所提方案的可行性与准确性。 相似文献
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Marcus T. Schmitz Bashir M. Al-Hashimi Petru Eles 《Design Automation for Embedded Systems》2002,6(4):401-424
In this paper, we introduce the LOPOCOS (Low Power Co-synthesis) system, a prototype CAD tool for system level co-design. LOPOCOS targets the design of energy-efficient embedded systems implemented as heterogeneous distributed architectures. In particular, it is designed to solve the specific problems involved in architectures that include dynamic voltage scalable (DVS) processors. The aim of this paper is to demonstrate how LOPOCOS can support the system designer in identifying energy-efficient hardware/software implementations for the desired embedded systems. Hence, highlighting the necessary optimization steps during design space exploration for DVS enable architectures. The optimization steps carried out in LOPOCOS involve component allocation and task/communication mapping as well as scheduling and dynamic voltage scaling. LOPOCOS has the following key features, which contribute to this energy efficiency. During the voltage scaling valuable power profile information of task execution is taken into account, hence, the accuracy of the energy estimation is improved. A combined optimization for scheduling and communication mapping based on genetic algorithm, optimizes simultaneously execution order and communication mapping towards the utilization of the DVS processors and timing behaviour. Furthermore, a separation of task and communication mapping allows a more effective implementation of both task and communication mapping optimizationsteps. Extensive experiments are conducted to demonstrate the efficiency of LOPOCOS. We report up to 38% higher energy reductions compared to previous co-synthesis techniques for DVS systems. The investigations include a real-life example of an optical flow detection algorithm. 相似文献
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Satoru Ibaraki Masao Fukushima Toshihide Ibaraki 《Computational Optimization and Applications》1992,1(2):207-226
A primal-dual version of the proximal point algorithm is developed for linearly constrained convex programming problems. The algorithm is an iterative method to find a saddle point of the Lagrangian of the problem. At each iteration of the algorithm, we compute an approximate saddle point of the Lagrangian function augmented by quadratic proximal terms of both primal and dual variables. Specifically, we first minimize the function with respect to the primal variables and then approximately maximize the resulting function of the dual variables. The merit of this approach exists in the fact that the latter function is differentiable and the maximization of this function is subject to no constraints. We discuss convergence properties of the algorithm and report some numerical results for network flow problems with separable quadratic costs. 相似文献
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This paper proposes a floating-point genetic algorithm (FPGA) to solve the unit commitment problem (UCP). Based on the characteristics of typical load demand, a floating-point chromosome representation and an encoding–decoding scheme are designed to reduce the complexities in handling the minimum up/down time limits. Strategic parameters of the FPGA are characterized in detail, i.e., the evaluation function and its constraints, population size, operation styles of selection, crossover operation and probability, mutation operation and probability. A dynamic combination scheme of genetic operators is formulated to explore and exploit the FPGA in the non-convex solution space and multimodal objective function. Experiment results show that the FPGA is a more effective technique among the various styles of genetic algorithms, which can be applied to the practical scheduling tasks in utility power systems. 相似文献