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61.
Lihong Huang 《Asian journal of control》2013,15(4):1158-1167
This paper considers a class of delayed neural networks with discontinuous neuron activations. Based on the theory of differential equations with discontinuous right‐hand sides, some novel sufficient conditions are derived that ensure the existence and global exponential stability of the equilibrium point. Moreover, by adopting the concept of convergence in measure, convergence behavior for the output is discussed. The obtained results are independent of the delay parameter and can be thought of as a generalization of previous results established for delayed neural networks with Lipschtz continuous neuron activations to the discontinuous case. Finally, we give a numerical example to illustrate the effectiveness and novelty of our results by comparing our results with those in the early literature. 相似文献
62.
基于二进制粒子群算法的异构传感器网络成本最优节点部署机制 总被引:1,自引:0,他引:1
节点部署作为无线传感器网络应用的一个核心问题,是保证网络服务质量的重要手段。针对异构传感器网络节点的高密度部署和监测目标的非均匀分布的情况,提出一种基于二进制粒子群算法的异构节点成本优化部署方法。该算法在满足区域节点部署要求的条件下以最小化传感器节点的部署成本为目标函数进行优化操作,以达到降低网络冗余、提高网络服务质量的效果。仿真结果表明,该算法能快速收敛于最优解,能够降低网络部署的成本,提高网络中目标监测的质量。 相似文献
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本文针对网络化数字媒体的版权保护提出了一种新的灰度水印图像嵌入到RGB彩色图像中的方法。首先将灰度水印图像进行置乱变换,再将置乱后的图像转换成二值序列,并将二值序列进一步分解成三个二值序列;然后将待嵌入水印的彩色图像分解成R、G、B三个分量,对每个分量分别作二级小波变换,得到小波变换的子带系数,再用奇偶判断法把三个二值序列的值分别嵌入各分量子带;最后用小波逆变换,恢复图像,合并三个分量,得到嵌入水印后的图像。仿真结果表明,本文方法有很好的透明性,且能有效的抵抗剪切、灰度调整、有损压缩等攻击。 相似文献
67.
We study the problem of segmenting a sequence into k pieces so that the resulting segmentation satisfies monotonicity or unimodality constraints. Unimodal functions can be used
to model phenomena in which a measured variable first increases to a certain level and then decreases. We combine a well-known
unimodal regression algorithm with a simple dynamic-programming approach to obtain an optimal quadratic-time algorithm for
the problem of unimodal k-segmentation. In addition, we describe a more efficient greedy-merging heuristic that is experimentally shown to give solutions
very close to the optimal. As a concrete application of our algorithms, we describe methods for testing if a sequence behaves
unimodally or not. The methods include segmentation error comparisons, permutation testing, and a BIC-based scoring scheme.
Our experimental evaluation shows that our algorithms and the proposed unimodality tests give very intuitive results, for
both real-valued and binary data.
Niina Haiminen received the M.Sc. degree from the University of Helsinki in 2004. She is currently a Graduate Student at the Department
of Computer Science of University of Helsinki, and a Researcher at the Basic Research Unit of Helsinki Institute for Information
Technology. Her research interests include algorithms, bioinformatics, and data mining.
Aristides Gionis received the Ph.D. degree from Stanford University in 2003, and he is currently a Senior Researcher at the Basic Research
Unit of Helsinki Institute for Information Technology. His research experience includes summer internship positions at Bell
Labs, AT&T Labs, and Microsoft Research. His research areas are data mining, algorithms, and databases.
Kari Laasonen received the M.Sc. degree in Theoretical Physics in 1995 from the University of Helsinki. He is currently a Graduate Student
in Computer Science at the University of Helsinki and a Researcher at the Basic Research Unit of Helsinki Institute for Information
Technology. His research is focused on algorithms and data analysis methods for pervasive computing. 相似文献
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In this paper, a class of non-autonomous reaction-diffusion neural networks with time-varying delays is considered. Novel methods to study the global dynamical behavior of these systems are proposed. Employing the properties of diffusion operator and the method of delayed inequalities analysis, we investigate global exponential stability, positive invariant sets and global attracting sets of the neural networks under consideration. Furthermore, conditions sufficient for the existence and uniqueness of periodic attractors for periodic neural networks are derived and the existence range of the attractors is estimated. Finally two examples are given to demonstrate the effectiveness of these results. 相似文献
70.
By using the continuation theorem of coincidence degree theory and constructing suitable Lyapunov functions, we study the existence, uniqueness and global exponential stability of periodic solutions for recurrent neural networks with impulsive perturbations and delays. Further, by using numerical simulation method, the influences of the impulsive perturbations on the inherent oscillations are investigated. 相似文献