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991.
双正交小波提升系数的递推算法与实现 总被引:1,自引:0,他引:1
根据双正交小波提升格式的特点,为了得到快速提升小波变换的系数,提出求解提升系数的递推算法。该方法基于前向小波变换的预测和更新过程的递推式,与给定双正交小波滤波器比较系数,求得小波提升系数和尺度系数。实例证明,无论是先预测后更新的提升格式,还是先更新后预测的提升格式,均可用此法求解提升系数。在Matlab7.0平台上,用递推算法编程实现db5.3小波转换成提升格式,完成图像的三级分解。 相似文献
992.
993.
GUO Junqi REN Shubo XIANG Haige 《电子学报:英文版》2008,(4):743-747
We propose a non-cyclic prefixed Single carrier frequency-domain equalization (SCFDE) system with Space-frequency block codes (SFBC). The transmitted signals in proposed system are composed of Singlecarrier (SC) information sequences derived from SFBC and training sequences, both of which have been placed in an alternate order without any Cyclic prefix (CP) before each SC information sequence. Furthermore, a recursire algorithm of Joint channel estimation and data detection (recursive-JCEDD) is proposed for system receiver. Simulation results show that the proposed non-cyclic prefixed SFBC-SCFDE system based on the recursive-JCEDD algorithm has better Bit error rate (BER) performance than traditional cyclic prefixed SFBC-SCFDE, Space-time block-coded SCFDE (STBC-SCFDE) and STBC-OFDM systems with some common channel estimation algorithms. 相似文献
994.
提出了一种基于下降的单纯形算法和模拟退火算法的混合优化算法用于反演地声参数。下降的单纯形方法对于目标函数的梯度信息相当敏感,因此在参数空间中能迅速地移向极小点,但由于它只能向下移动,因而往往易陷入局部极小且依赖初始条件。而模拟退火算法使用随机选取的目标函数值在参数空间中搜索最佳答案,其结构有利于从局部极小中跳出,但是由于它不能利用目标函数的梯度信息因而对参数空间的搜索效率很低。混合方法结合了下降的单纯形方法与快速模拟退火方法这二者的优点,能更有效、更迅速地获得全局最优点。 相似文献
995.
996.
何田 《电子工业专用设备》2006,36(2):53-57
以半导体生产设备为代表的现代高速精密机电设备中普遍采用主-从式计算机控制的模式,从机以嵌入方式包含在设备中而不便于其上所运行的运动控制算法实时状态的监测;运动控制算法本身复杂度的不断增加进一步提高了代码高效调试的难度,对最短时间内获得运行正确的运动控制代码提出了极大的挑战。提出了一种能够准确反映控制对象真实响应的运动控制算法实时仿真和调试方法。该方法将从机DSP上运行的运动控制算法完整不变地转移到主机上运行,并且对DSP代码的输入输出函数进行少量修改以利用数值积分方法模拟控制对象的响应,实现了从机DSP运动控制算法和主机程序在同一计算机处理器上以真实的实时状态运行并且可以象普通源代码一样进行方便有效的单步、断点等调试。该方法可以与各种数据可视化手段相结合,形成完整、直观、高效的,完全脱离从机和控制对象的运动控制算法虚拟实时仿真调试环境。给出了该方法在半导体生产设备上成功应用的例子。该方法适用于各种独立运行于嵌入式处理器的运动控制算法的仿真调试。 相似文献
997.
In this article, a genetic evolutionary algorithm is proposed for efficient allocation of wavelength converters in WDM optical
networks. Since wavelength converters are expensive, it is desirable that each node in WDM optical networks uses a minimum
number of wavelength converters to achieve a near-ideal performance. The searching capability of genetic evolutionary algorithm
has been exploited for this purpose. The distinguished feature of the proposed approach lies in handling the conflicting circumstances
during allocation of wavelength converters considering various practical aspects (e.g., spatial problem, connectivity of a
node with other nodes) rather than arbitrarily to possibly improve the overall blocking performance of WDM optical networks.
The proposed algorithm is compared with a previous approach to establish its effectiveness and the results demonstrate the
ability of the proposed algorithm to efficiently solve the problem of Optimal Wavelength Converters Allocation (OWCA) in practical
WDM optical networks.
相似文献
Mrinal K. NaskarEmail: |
998.
Dynamic restoration algorithms which support real-time and multi-services recovery are significant for the survivability of
WDM (wavelength division multiplexed) networks. In this article, an intelligent dynamic restoration algorithm for multi-services
in WDM networks based on the partheno genetic algorithm is proposed. In these networks, partial wavelength conversion is used.
The algorithm is implemented within an interconnected multilayer-graph model and two kinds of optical networks matrix models.
Compared with the basic restoration scheme, the proposed algorithm can make use of available network state information and
can restore the affected multi-services fast and parallel. Simulation showed that the proposed algorithm can improve the restoration
efficiency under high loads and reduce the service disruption ratio on the basis of fully utilizing resources of the network.
相似文献
Na ZhuEmail: |
999.
在分析现有单站无源定位方法优缺点的基础上,提出了一种基于无源测距的快速定位方法,该方法具有定位精度较高、收敛速度较快等优点。这种处理思路还可以推广到更为复杂的定位情况中去。 相似文献
1000.
Depending on whether bidirectional links or unidirectional links are used for communications, the network topology under a
given range assignment is either an undirected graph referred to as the bidirectional topology, or a directed graph referred
to as the unidirectional topology. The Min-Power Bidirectional (resp., Unidirectional) k-Node Connectivity problem seeks a range assignment of minimum total power subject to the constraint that the produced bidirectional
(resp. unidirectional) topology is k-vertex connected. Similarly, the Min-Power Bidirectional (resp., Unidirectional) k-Edge Connectivity problem seeks a range assignment of minimum total power subject to the constraint the produced bidirectional
(resp., unidirectional) topology is k-edge connected.
The Min-Power Bidirectional Biconnectivity problem and the Min-Power Bidirectional Edge-Biconnectivity problem have been studied
by Lloyd et al. [23]. They show that range assignment based the approximation algorithm of Khuller and Raghavachari [18],
which we refer to as Algorithm KR, has an approximation ratio of at most 2(2 – 2/n)(2 + 1/n) for Min-Power Bidirectional Biconnectivity, and range assignment based on the approximation algorithm of Khuller and Vishkin [19],
which we refer to as Algorithm KV, has an approximation ratio of at most 8(1 – 1/n) for Min-Power Bidirectional Edge-Biconnectivity.
In this paper, we first establish the NP-hardness of Min-Power Bidirectional (Edge-) Biconnectivity. Then we show that Algorithm KR has an approximation ratio of at most 4 for both Min-Power Bidirectional Biconnectivity and Min-Power Unidirectional Biconnectivity,
and Algorithm KV has an approximation ratio of at most 2k for both Min-Power Bidirectional k-Edge Connectivity and Min-Power Unidirectional k-Edge Connectivity. We also propose a new simple constant-approximation algorithm for both Min-Power Bidirectional Biconnectivity
and Min-Power Unidirectional Biconnectivity. This new algorithm applies only to Euclidean instances, but is best suited for
distributed implementation.
A preliminary version of this work appeared in the proceedings of the 2nd International Conference on AD-HOC Network and Wireless
(Adhoc-Now 2003).
Research performed in part while visiting the Max-Plank-Institut fur Informatik.
Gruia Calinescu is an Assistant Professor of Computer Science at the Illinois Institute of Technology since 2000. He held postdoc or visiting
researcher positions at DIMACS, University of Waterloo, and Max-Plank Institut fur Informatik. Gruia has a Diploma from University
of Bucharest and a Ph.D. from Georgia Insitute of Technology. His research interests are in the area of algorithms.
Peng-Jun Wan has joined the Computer Science Department at Illinois Institute of Technology in 1997 and has been an Associate Professor
since 2004. He received his Ph.D. in Computer Science from University of Minnesota in 1997, M.S. in Operations Research and
Control Theory from Chinese Academy of Science in 1993, and B.S. in Applied Mathematics from Tsinghua University in 1990.
His research interests include optical networks and wireless networks. 相似文献