The Robustness of Stochastic Switching Networks

被引:6
|
作者
Loh, Po-Ling [1 ]
Zhou, Hongchao [2 ]
Bruck, Jehoshua [2 ]
机构
[1] CALTECH, Dept Math, Pasadena, CA 91125 USA
[2] CALTECH, Dept Elect Engn, Pasadena, CA 91125 USA
基金
美国国家科学基金会;
关键词
D O I
10.1109/ISIT.2009.5205379
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Many natural systems, including chemical and biological systems, can be modeled using stochastic switching circuits. These circuits consist of stochastic switches, called pswitches, which operate with a fixed probability of being open or closed. We study the effect caused by introducing an error of size epsilon to each pswitch in a stochastic circuit. We analyze two constructions-simple series-parallel and general series-parallel circuits-and prove that simple series-parallel circuits are robust to small error perturbations, while general series-parallel circuits are not. Specifically, the total error introduced by perturbations of size less than epsilon is bounded by a constant multiple of e in a simple series-parallel circuit, independent of the size of the circuit. However, the same result does not hold in the case of more general series-parallel circuits. In the case of a general stochastic circuit, we prove that the overall error probability is bounded by a linear function of the number of pswitches.
引用
收藏
页码:2066 / +
页数:2
相关论文
共 50 条
  • [31] The Stability of Impulsive Stochastic Delay Neural Networks with Markovian Switching
    带马氏切换的时滞脉冲神经网络稳定性分析
    [J]. Xu, Chang (692961142@qq.com), 1600, Beijing Institute of Technology (40): : 1133 - 1137
  • [32] Partial synchronization in stochastic dynamical networks with switching communication channels
    Huang, Chi
    Ho, Daniel W. C.
    Lu, Jianquan
    Kurths, Juergen
    [J]. CHAOS, 2012, 22 (02)
  • [33] Asymptotic boundedness for stochastic coupled systems on networks with Markovian switching
    Zhang, Chunmei
    Li, Wenxue
    Su, Huan
    Wang, Ke
    [J]. NEUROCOMPUTING, 2014, 136 : 180 - 189
  • [34] ROBUST EXPONENTIAL STABILIZATION OF STOCHASTIC NEURAL NETWORKS WITH MARKOVIAN SWITCHING
    Jiang, Guo-Cai
    Zhong, Shou-Ming
    [J]. 2008 INTERNATIONAL CONFERENCE ON APPERCEIVING COMPUTING AND INTELLIGENCE ANALYSIS (ICACIA 2008), 2008, : 100 - 105
  • [35] Time Synchronization of Wireless Sensor Networks with Stochastic Switching Topology
    Yin, Haian
    Xie, Wen
    Wang, He
    [J]. PROCEEDINGS OF THE 28TH CHINESE CONTROL AND DECISION CONFERENCE (2016 CCDC), 2016, : 4085 - 4090
  • [36] Passivity analysis of stochastic delayed neural networks with Markovian switching
    Zhu, Song
    Shen, Yi
    [J]. NEUROCOMPUTING, 2011, 74 (10) : 1754 - 1761
  • [37] Bilateral Teleoperation Over Networks Based on Stochastic Switching Approach
    Walker, Kevin C.
    Pan, Ya-Jun
    Gu, Jason
    [J]. IEEE-ASME TRANSACTIONS ON MECHATRONICS, 2009, 14 (05) : 539 - 554
  • [38] A simple stochastic model for complex coextinctions in mutualistic networks: robustness decreases with connectance
    Vieira, Marcos Costa
    Almeida-Neto, Mario
    [J]. ECOLOGY LETTERS, 2015, 18 (02) : 144 - 152
  • [39] Data-Enabled Stochastic Modeling for Evaluating Schedule Robustness of Railway Networks
    Khadilkar, Harshad
    [J]. TRANSPORTATION SCIENCE, 2017, 51 (04) : 1161 - 1176
  • [40] CONSENSUS IN NETWORKS OF MULTIAGENTS WITH SWITCHING TOPOLOGIES MODELED AS ADAPTED STOCHASTIC PROCESSES
    Liu, Bo
    Lu, Wenlian
    Chen, Tianping
    [J]. SIAM JOURNAL ON CONTROL AND OPTIMIZATION, 2011, 49 (01) : 227 - 253