搜索资源列表
HMM-and-FMM
- 正向最大匹配算法和逆向最大匹配算法，词典也放进来了-Forward and reverse maximum matching algorithm maximum matching algorithm, the dictionary also put to the
hmmdecode
- 主要用来计算给定观测序列的概率（求解HMM中的第一个问题）-Mainly used to calculate the probability of a given observation sequence (HMM solving the first problem)
hmmestimate
- 给定观测序列和状态序列下估计HMM模型的参数-Given the HMM parameters under observation sequence and state sequence estimation
hmmtrain
- 隐马尔可夫模型参数的极大似然估计,用来求解HMM的第三个问题-HMM maximum likelihood parameter estimates used to solve the third problem HMM
0002HMM
- 利用隐马尔科夫方法进行人脸识别，具有较高的识别精度-use the HMM to human face recognition
Hidden-Markov
- 关于隐马尔科夫模型方面的文献资料，介绍了HMM的原理，拓展。创新性将SVM和HMM结合应用-Literature on hidden Markov model aspects, introduced the principle of HMM expand. The innovative application of SVM and HMM combination
UMDHMM-python-master
- 1870年，俄国有机化学家Vladimir V. Markovnikov第一次提出马尔科夫模型 -hmm python
HMMDemo
- 基于HMM算法实现人脸识别，利用opencv开源视觉库来实现人脸识别-Face recognition algorithm based on HMM
hmm
- 隐马尔科夫实现代码，包括前进算法，和前进后退算法-Hidden Markov implementation code
off-line-signature-verification
- 是离线签名鉴别系统，是利用HMm做的，Hmm法是把签名过程看成是一个随机过程-Offline signature verification systems is the use of HMm do，Hmm signature method is to be seen as a stochastic process procedure
Markov
- Java实现的一个隐马尔科夫模型，该模型可用于一般的教学，相比其他的大型的HMM库更容易理解。-A hidden Markov model implemented in Java, this model can be used for general education, compared to other large HMM library easier to understand.
MovieTest
- 改程序为Java实现的一个HMM模型用于经典数据集MovieLens的实践，用于预测人们的观影倾向。-Reform program is a Java implementation of HMM model for classic dataset MovieLens practice, used to predict people s viewing tendencies.
network
- 多种神经网络算法，包括等，可实现模式识别以及回归。-There are many algorithms in the zip,including svm, bp, crf,hmm.It can be used in the pattern recognition.
viterbi-algorithm
- 用Viterbi算法来解码隐马尔科夫模型(HMM)的状态变量。其中，mainfile_Vit.m是主函数，Viterbi_algorithm.m是调用的Viterbi算法函数。-Viterbi algorithm for decoding the hidden states of the Hidden Markov Model(HMM). In this folder, "mainfile_Vit.m" file is the main function, and "Viterbi_algori
Baum_Welch-algorithm
- 用Baum-Welch算法来迭代估计一个隐马尔科夫模型（HMM）的初始状态概率分布以及其状态转移概率矩阵。其中文件有mainfile_B_W.m为主函数，Baum_Welch.m为Baum-Welch算法迭代函数，Forward_variable.m与Backward_variable.m与Gamma_variable.m与Ksi_variable.m是需要计算的四种因子，B_pdf.m为混淆散射概率密度函数。-It s Baum-Welch algorithm for iteratively
voice-recognition
- 实现基于MFCC和HMM及Viterbi的语音识别系统，识别率可达到80 以上-MFCC and HMM-based speech recognition systems and Viterbi recognition rate can reach 80
matching-Chinese-word-by-HMM-and-MM
- 该程序为在MFC下开发的正向和反向两种中文分词系统。-The program was developed in MFC under both positive and negative Chinese word segmentation system.
HTS-Introduction
- An Introduction to HMM-Based (hidden Markov model) Speech Synthesis
htk-3.3
- HTK是英国剑桥大学开发的一套基于C语言的隐马尔科夫模型工具箱，主要应用于语音识别、语音合成的研究，也被用在其他领域，如字符识别和DNA排序等。HTK是重量级的HMM版本。-Cambridge University HTK is a C-based language developed by the Hidden Markov Model Toolkit, mainly used in speech recognition, speech synthesis research, has also
train
- 这是HMM算法里的训练功能的程序，是EM算法中的一种，即前向后向算法。-This is where the training function HMM algorithm procedure is an EM algorithm, the algorithm back before that.