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hsmm
- 隐半马尔可夫模型，应用范围很广，我主要应用于大型网站访问行为异常检测的建模。
hsmm_new
- 提供HSMM隐半马尔科夫的前向后向算法。可用于模式识别-Hidden semi-Markov providing HSMM back to the first algorithm. Can be used for pattern recognition
mattjj-matlab-hsmm-40a597a
- Bayesian-HSMM it is very useful. in fact, it extended tranditional HSMM. it contains a example, if you want to used it, please run demo.-a matalab code based on Bayesian-HSMM. it is very useful. in fact, it extended tranditional HSMM. it contains
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- 轴承全寿命数据的各种时域频域特征提取，包括17个时域和13个频域特征-Bearing a variety of life-cycle data in time domain frequency domain feature extraction
hsmm_0.3-5.tar
- Hidden SemiMarkov models 主要是改进HMM存在状态保持时间的局限性，引入了持续时间的函数显式表达-Hidden SemiMarkov models was mainly to improve HMM state of existence to maintain the limitations of time, the introduction of an explicit function of the duration of expression of
HSMM
- 实现HMM的前向算法,作为HMM三个算法的一部分，其他的包括检测算法和训练算法。-finish the forward of HMM，it is one part of three Arithmetic of HMM.
HSMM
- 隐半马尔可夫模型，只要替换原有的参数就能计算。可以用于模式识别，剩余寿命预测等-Half hidden markov model, as long as replacing the original parameters can be calculated. Can be used in pattern recognition, the residual life prediction, etc
hsmm_new
- hsmm的matlab例子，提供了各种说明函数，注释丰富-hsmm matlab example
231738171039948
- 此为HSMM算法的实现代码，只要修改初始参数就可以运行，希望多多交流(This is the implementation code of the HSMM algorithm. It can be run as long as the initial parameters are modified. It is hoped that there will be more exchanges.)
hsmm
- 隐马尔科夫模型是关于时序的概率模型，描述由一个隐藏的马尔科夫链随机生成不可观测的状态随机序列，再由各个状态生成一个观测而产生观测序列的过程。隐藏的马尔科夫链随机生成的状态的序列，称为状态序列；每个状态生成一个观测，而由此产生的观测的随机序列，称为观测序列。马尔科夫链由初始概率分布、状态转移概率分布以及观测概率分布确定(The hidden Markov model is a probabilistic model for time series. It describes the process
Bayesian and HSMM
- 贝叶斯HSMM 主要是改进HMM存在状态保持时间的局限性，引入了持续时间的函数显式表达，用贝叶斯概率估计((Bayesian and HSMM was mainly to improve HMM state of existence to maintain the limitations of time, the introduction of an explicit function of the duration of expression of))
HSMM
- 隐半马尔科夫模型matlab算法,改进的隐马尔可夫模型，增加了状态停留时间(hidden semi-markvo model Add state duration)