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- adaptive particle filter 自适应粒子滤波
- Adaptive particle filtering 自适应滤波
- 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。
- 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。
- 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。
- 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。
- 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。
- According to the key technique influencing the particle filter, a Gassian mixture particle filter for non-rigid object tracking is presented. 针对影响粒子滤波算法性能的关键技术，提出了基于混合高斯模型的粒子滤波算法，并将其用于基于颜色的非刚性目标的实时跟踪相关问题。
- 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。
- To improve the passive tracking performance of 2D maneuvering target, a new constraint particle filter (CPF) is proposed. 摘要为提高约束条件下的二维机动目标被动跟踪性能，提出了一种约束下的粒子滤波方法(CPF)。
- According to the key technique influencing the particle filter,a Gassian mixture particle filter for non-rigid object tracking is presented. 针对影响粒子滤波算法性能的关键技术,提出了基于混合高斯模型的粒子滤波算法,并将其用于基于颜色的非刚性目标的实时跟踪相关问题。
- The particle filter can deal with nonlinear/non-Guassian problems and it has been introduced to the algorithm of IMM for higher precision. 粒子滤波能够处理非线性/非高斯问题，其与交互式多模型结合用来获得更好的跟踪性能。
- A multiple model particle filter algorithm is presented in this paper for the maneuvering weak target which dynamics is complicated. 该文针对目标作复杂运动的情况，提出了机动弱目标检测前跟踪的多模粒子滤波算法。
- Abstract : Aiming at the shortcoming of particle dry in traditional particle filter, an improved cost reference particle filter(CRPF) was proposed. 摘要： 针对传统粒子滤波算法中粒子枯竭的缺陷，提出了一种改进的代价参考粒子滤波(CRPF)方法。
- To overcome the sample impoverishment problem of particle filter, the observation vector of H infinity filter is regularized. 为解决粒子滤波的“采样枯竭”问题，正则化了H无穷粒子滤波器的观测矢量。
