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coforest
- CoForest是一种半监督算法，处理集成学习及利用大量未标记数据得到更优越性能的假设。-CoForest is a semi-supervised algorithm, which exploits the power of ensemble learning and large amount of unlabeled data available to produce hypothesis with better performance.
HMM
- This paper presents a hybrid framework of feature extraction and hidden Markov modeling (HMM) for two-dimensional pattern recognition. Importantly, we explore a new discriminative training criterion to assure model compactness and discriminability. T
moments
- Mahler发表的概率假设密度滤波和随机集领域的开创性文章-It is presened by Prof.Mahler for the probability hypothesis density filter and finite random set
GM_PHDpaper
- IEEE trans. 发表的高斯概率假设密度滤波的开创性文章-It is published in an IEEE tans. on Gaussian mixture probability hypothesis density filter and finite random set
PF_PHDpaper
- 粒子滤波实现的概率假设密度滤波和随机集领域的开创性文章，发表于IEEE trans-It is presened on the particle filter for the probability hypothesis density filter and finite random set
closeForm_PHD
- IEEE trans上发表的高斯混合概率假设密度滤波的证明性论文-It is presened for the GM probability hypothesis density filter and finite random set
MHT
- 程序对多目标跟踪进行了仿真，运用的是多假设模型-Procedures for multi-target tracking simulation, the use of multiple hypothesis model
7-9
- 分别介绍了概率与数理统计概述、统计估计、假设检验、方差分析、回归分析、正交试验分析、聚类分析、判别分析和多元数据相关分析等内容，理论与实践相结合，向读者演示了matlab在数理统计中的应用。(It respectively introduces the outline of probability and mathematical statistics, statistical estimation, hypothesis test, variance analysis, regression