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粒子滤波是基于序贯Monte Carlo 仿真方法的非线性滤波算法，对基本粒子滤波算法的原理实现步骤进行了详细的介绍，进行了仿真试验。-Particle filter is based on sequential Monte Carlo simulation method of nonlinear filtering algorithm, the principle of elementary particle filter algorithm to achieve a detailed int
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monte carlo simulation estimate and error probability ploting for a binary communication system employing matched filter
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介绍了三点垂直线阵被动定位的原理. 结合矢量水听器测得的方位角和高低角及到达
阵元间的时延差, 建立了三维坐标下的状态方程和观测方程.运用扩展卡尔曼滤波算法, 研究了该系统的目标运动分析问题. 通过蒙特卡洛模拟仿真试验, 结果表明上述方法具有较高的定位性能,有较强的使用价值.
-Introduced three vertical linear array passive location principle of vector hydrophone. Combining the meas
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粒子滤波是基于递推的蒙特卡罗模拟方法的总称，可用于任意非线性，非高斯随机系统的状态估计。-The particle filter is based on recursive Monte Carlo simulation method general, can be used for any non-linear, non-Gaussian random system state estimation.
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the program based on particle filter for a new algorithm, Integrated Bayesian MCMC Model Selection MONTE CARLO that Ma Erkefu chain
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the program based on particle filter for a new algorithm, Integrated Bayesian MCMC Model Selection MONTE CARLO that Ma Erkefu chain
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the program based on particle filter for a new algorithm, Integrated Bayesian MCMC Model Selection MONTE CARLO that Ma Erkefu chain
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the program based on particle filter for a new algorithm, Integrated Bayesian MCMC Model Selection MONTE CARLO that Ma Erkefu chain
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定位技术是无线传感器网络中关键的基础支撑技术, 目前提出了许多静态网络的节点定位算
法, 移动无线传感器网络的定位研究相对较少. 针对定位节点和参考节点随机运动的网络模型, 提出了
一个基于动态网格划分的蒙特卡罗定位算法. 算法中当接收的参考节点数超过一定阈值时使用最远距
离节点选择模型, 选出部分参考节点参与定位和信息转发, 节约能耗. 接着基于选择的或所有接收的参
考节点构建采样区域, 进行网格划分, 使用网格单元数计算最大采样次数, 在采样区域内采样并使用误
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As the computer hardware developing and the fast advances of computers in the last several years, Monte Carlo particle filter
algorithms, which origin Monte Carlo methods, have become popular again. The Monte Carlo particle filter algorithms in thi
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