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| 1 | Convergence Rate Analysis of Gaussian Belief Propagation for Markov Networks显示文摘Gaussian belief propagation algorithm(GaBP) is one of the most important distributed algorithms in signal processing and statistical learning involving Markov networks. It is well known that the algorithm correctly computes marginal density functions from a high dimensional joint density function over a Markov network in a finite number of iterations when the underlying Gaussian graph is acyclic. It is also known more recently that the algorithm produces correct marginal means asymptotically for cyclic Gaussian graphs under the condition of walk summability(or generalised diagonal dominance). This paper extends this convergence result further by showing that the convergence is exponential under the generalised diagonal dominance condition,and provides a simple bound for the convergence rate. Our results are derived by combining the known walk summability approach for asymptotic convergence analysis with the control systems approach for stability analysis. | Zhaorong Zhang Minyue Fu | 2020 | IEEE/CAA Journal of Automatica Sinica2020，7，3： | 2 |
| 2 | 改进粒子群算法和动态窗口法的动态路径规划显示文摘针对粒子群算法收敛速度慢、精度低以及只适用于静态环境等问题,提出改进粒子群-差分进化和动态窗口法的混合算法.首先利用差分进化算法改进粒子群算法寻优机制,对粒子群算法进行优化,构造新的适应度函数,实现对全局的路径规划;然后,根据生成的路径,提取关键中节点作为动态窗口法的局部目标点,采用动态窗口法进行局部路径规划,使起始航向角继承上一次到达局部目标点的航向角,生成从起始点到目标点的最短且平滑的路径.最后,将所提算法应用于不同试验场景进行路径规划仿真试验,并与现有算法进行对比分析,结果表明所提算法可行性强,具有更高的搜索能力. | 孙睿彤 袁庆霓 衣君辉 白欢 | 2023 | 小型微型计算机系统2023，44，8： | 2 |
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