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混沌时间序列预测
- 1、该工具箱包括了混沌时间序列分析与预测的常用方法,有: (1)产生混沌时间序列(chaotic time series) Logistic映射 - \ChaosAttractors\Main_Logistic.m Henon映射 - \ChaosAttractors\Main_Henon.m Lorenz吸引子 - \ChaosAttractors\Main_Lorenz.m Duffing吸引子 - \ChaosAttractors\Main_Duffing.m Duffin
IDASimulation
- 本文针对SLAM数据关联中使用最为广泛的最近邻方法作了改进，利用特征估计位置与载体预测位置之间的欧氏距离计算代替了全部特征与每个量测之间的马氏距离计算，避免了大量的矩阵乘法计算。该算法简单易行，降低了算法的计算复杂度，有利于SLAM算法的实时执行，且关联效果与全局最近邻法相同-In this paper, SLAM data association in the most widely used methods of improving the nearest neighbor, using t
cv_pdaf
- CV模型，利用概率数据关联算法和最近邻算法对其进行跟踪滤波，保证正确-CV model, the probabilistic data association algorithm and the nearest neighbor filter algorithm to track and ensure the correct
PDANN
- 杂波环境下单目标跟踪算法，包括概率数据关联和最近邻算法。-Single target tracking methods in clutter environment, including PDA and NN
data-asso--introduction
- 详细介绍数据关联的相关知识，包含最近邻，JPDA的算法的详细推导。-Detailed data related knowledge, including the nearest neighbor, detailed derivation JPDA algorithm.
NNDA
- 用matlab编写的最近邻域的数据关联，采用kalman滤波实现-Associated with the most recent data prepared matlab neighborhood, using kalman Filtering
NNCJPDA_confirmed
- 这个函数用于多目标跟踪数据关联，结合了最近邻数据关联个CJPDA数据关联算法，每个目标分配最多一个量测-This function is used for multi-target tracking data association, combined with nearest neighbor data association a CJPDA data association algorithm, each target allocation up to a measurement