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- Adaptive particle filtering 自适应滤波
- adaptive particle filter 自适应粒子滤波
- Aiming at the existing problems of current multi-model algorithm for maneuvering target tracking, the paper proposes a model adaptive maneuvering target tracking algorithm based on particle filtering. 摘要针对当前机动目标跟踪领域中多模型算法存在的问题，提出一种基于粒子滤波的模型自适应机动目标跟踪算法。
- Unscented particle filtering algorithm using minimal skew sampling[J]. 引用该论文 刘贵喜;马涛;陈石磊.
- The application of the landscape adaptive particle swarm optimizer(LAPSO),which combines these two schemes,was studied. 空间自适应粒子群优化算法(LAPSO)有机融合上述2种改进机制。
- adapted particle filter 自适应粒子滤波
- Particle filter tracking algorithm based on maximum a posteriori[J]. 引用该论文 刘天键;朱善安.
- A demo illustring Particle filter for navigation with altimetric measurements. 这个程序通过粒子滤波实现地形辅助导航算法。
- In order to solve the premature convergence problem of particle swarm optimization，a novel fuzzy adaptive Particle Swarm Optimization based on T-S model（T-SPSO） is presented. 摘要 针对微粒群优化算法存在的早熟问题，提出了一种基于T-S模型的模糊自适应PSO算法（T-SPSO算法）。
- The adaptive particle swarm optimization is used to optimize the parameters of SVM so as to avoid artificial arbitrariness and enhance the forecast accuracy. 同时利用粒子群算法优化小波最小二乘支持向量机的参数，避免了人为选择参数的盲目性，从而提高了模型的预测精度。
- Firstly, the covariance of targets is calculated by the method of particle filtering. 该方法首先利用粒子滤波计算目标的协方差；
- To improve the performance of passive tracking for maneuvering target in clutter,a new particle filtering algorithm for passive tracking is proposed. 为提高杂波条件下的机动目标被动跟踪的性能,提出了一种新的粒子滤波目标被动跟踪算法。
- Data fusion of SINS/GPS integrated navigation system is realized using the Gaussian particle filter (GPF) and a direct filtering model. 摘要利用高斯粒子滤波技术和直接滤波模型实现了SINS/GPS组合导航系统的数据融合。
- The paper presented the parallel cluster algorithm of adaptive particle swarm optimization, which adopted task parallelization and partial asynchronous communication to decrease the computing time. 摘要提出了基于自适应微粒群优化的并行聚类算法，采用了任务分布方案和部分异步并行通信，降低了计算时间。
- The paper presented the parallel cluster algorithm of adaptive particle swarm optimization,which adopted task parallelization and partial asynchronous communication to decrease the computing time. 提出了基于自适应微粒群优化的并行聚类算法,采用了任务分布方案和部分异步并行通信,降低了计算时间。
- A particle filter algorithm based on Bayesian theory and Monte-Carlo simulation is presented. 提出了一种基于贝叶斯理论及蒙特卡罗仿真的粒子滤波算法。
- The simulation results show that the improved particle filter can effectively track the highly maneuvering targets. 仿真结果证实，该改进算法能有效跟踪高度机动的目标。
- This dissertation introduces particle filter into the problem of data fuse between sensor nodes. 本文针对传感器节点之间数据融合的问题，引入了粒子滤波算法。
- Such particle filters can reduce soot emissions by as much as 98 percent. 这类微粒过滤器，可使煤灰减少98%25之多。
