Description: HMM(Hidden Markov Model)，狀態數目N=3，觀察符號數目M=2，時間長度T=3。
(a) Probability Evaluation: 給定狀態轉換機率A、狀態符號觀察機率B、和起始機率 ，求觀察序列 出現的機率。
(b) Optimal State Sequence: 給定狀態轉換機率A、狀態符號觀察機率B、起始機率 、和觀察序列 ，求一個狀態序列 使得O出現的機率最大。
(c) Parameter Estimation: 給定狀態轉換機率A、狀態符號觀察機率B、起始機率 、和觀察序列 ，求新的A、B、 ，使得O出現的機率最大。
-HMM (Hidden Markov Model), state the number of N = 3, Observation number of symbols M = 2, T = length of three. (A) Probability Evaluation : given state transition probability A, Observer status symbol probability of B, and initial probability for observation sequence in the octave. (B) Optimal State Sequence : given state transition probability A, Observer status symbol probability of B, the initial probability, and observation sequence, for a state sequence of O makes the greatest risk. (C) Parameter Estimation : given state transition probability A, Observer status symbol probability of B, the initial probability, and observation sequence, the way the A, B, and O makes the greatest risk. Platform: |
Size: 146567 |
Author:章勝鈞 |
Hits:
Description: CHMMBOX, version 1.2, Iead Rezek, Oxford University, Feb 2001
Matlab toolbox for max. aposteriori estimation of two chain
Coupled Hidden Markov Models.
-CHMMBOX, version 1.2, Iead Rezek, Oxford University, Feb 2001 Matlab toolbox for max. aposteriori es timation of two chain Coupled Hidden Markov Mod els. Platform: |
Size: 823205 |
Author:Joyce |
Hits:
Description: HMM(Hidden Markov Model)，狀態數目N=3，觀察符號數目M=2，時間長度T=3。
(a) Probability Evaluation: 給定狀態轉換機率A、狀態符號觀察機率B、和起始機率 ，求觀察序列 出現的機率。
(b) Optimal State Sequence: 給定狀態轉換機率A、狀態符號觀察機率B、起始機率 、和觀察序列 ，求一個狀態序列 使得O出現的機率最大。
(c) Parameter Estimation: 給定狀態轉換機率A、狀態符號觀察機率B、起始機率 、和觀察序列 ，求新的A、B、 ，使得O出現的機率最大。
-HMM (Hidden Markov Model), state the number of N = 3, Observation number of symbols M = 2, T = length of three. (A) Probability Evaluation : given state transition probability A, Observer status symbol probability of B, and initial probability for observation sequence in the octave. (B) Optimal State Sequence : given state transition probability A, Observer status symbol probability of B, the initial probability, and observation sequence, for a state sequence of O makes the greatest risk. (C) Parameter Estimation : given state transition probability A, Observer status symbol probability of B, the initial probability, and observation sequence, the way the A, B, and O makes the greatest risk. Platform: |
Size: 146432 |
Author:章勝鈞 |
Hits:
Description: CHMMBOX, version 1.2, Iead Rezek, Oxford University, Feb 2001
Matlab toolbox for max. aposteriori estimation of two chain
Coupled Hidden Markov Models.
-CHMMBOX, version 1.2, Iead Rezek, Oxford University, Feb 2001 Matlab toolbox for max. aposteriori es timation of two chain Coupled Hidden Markov Mod els. Platform: |
Size: 823296 |
Author:Joyce |
Hits:
Description: EM算法（英文）A Gentle Tutorial of the EM Algorithm
and its Application to Parameter
Estimation for Gaussian Mixture and
Hidden Markov Models-A Gentle Tutorial of the EM Algorithm
and its Application to Parameter
Estimation for Gaussian Mixture and
Hidden Markov Models Platform: |
Size: 99328 |
Author:雷雷 |
Hits:
Description: EM算法简明教程 用于高斯分布隐马尔可夫模型的参数估计-Gentle Tutorial of the EM Algorithm and its Application to Parameter Estimation for Gaussian Mixture and Hidden Markov Models Platform: |
Size: 99328 |
Author:hou |
Hits:
Description: The book: Hidden Markov Models - Estimation and Control.
Applications and interest in Hidden Markov Models continues to grow. The authors have been pleased with the reception of the first edition of this book. Following comments and feedback from friends, students and others working
with Hidden Markov Models the second edition contains clarifications, improvements
and some new material.-The book: Hidden Markov Models- Estimation and Control.
Applications and interest in Hidden Markov Models continues to grow. The authors have been pleased with the reception of the first edition of this book. Following comments and feedback from friends, students and others working
with Hidden Markov Models the second edition contains clarifications, improvements
and some new material. Platform: |
Size: 4501504 |
Author:Dang Tran Vu |
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Description: 采用Baum-Welch重估计算法对隐马尔科夫模型进行训练，使得结果达到最优化-Using Baum-Welch re-estimation algorithm for training hidden Markov models, making the results of optimized Platform: |
Size: 16384 |
Author:king |
Hits:
Description: the newer version from HMMbox 3.2
Matlab toolbox for Variational estimation Hidden Markov Models.
(Adapted from Hidden Markov Toolbox Version 3.3 01-Apr-99 and
Coupled Hidden Markov Toolbox Version 1.1 01-Feb-01
Copyright (c) by Iead Rezek, Oxford University)
The software uses some NETLAB routines
(see http://neural-server.aston.ac.uk/netlab/index.html
so you ll need to have NETLAB on your search path
See the file VERSION for what s new in this version.
The observation models has so far been implemented are
Gaussian, Poisson and Dirichlet
-the newer version from HMMbox 3.2
Matlab toolbox for Variational estimation Hidden Markov Models.
(Adapted from Hidden Markov Toolbox Version 3.3 01-Apr-99 and
Coupled Hidden Markov Toolbox Version 1.1 01-Feb-01
Copyright (c) by Iead Rezek, Oxford University)
The software uses some NETLAB routines
(see http://neural-server.aston.ac.uk/netlab/index.html
so you ll need to have NETLAB on your search path
See the file VERSION for what s new in this version.
The observation models has so far been implemented are
Gaussian, Poisson and Dirichlet
Platform: |
Size: 164864 |
Author:iwan |
Hits:
Description: 这是张德丰《MATLAB概率与数理统计分析》随书源码(M文件)。代码包括的内容有：概率分布计算及统计特征、数字特征计算、统计图绘制(盒状图、散度图等)、点估计和区间估计、假设检验、方差分析、曲线拟合、回归分析、因素分析、聚类分析、正交实验设计分析、多元方差分析、判别分析、隐马尔可夫模型建模与参数估计和在语音识别中的应用。-This is Zhang Defeng " MATLAB Analysis of probability and mathematical statistics," with the book source (M file). The contents of the code include: calculation of the probability distribution and statistical characteristics, digital feature calculation, statistical mapping (box-shaped graph, scatter graph, etc.), point and interval estimation, hypothesis testing, analysis of variance, curve fitting, regression analysis, factor analysis, cluster analysis, orthogonal experimental design, multivariate analysis of variance, discriminant analysis, hidden Markov modeling and parameter estimation and application in speech recognition. Platform: |
Size: 32768 |
Author:吴 |
Hits:
Description: A Gentle Tutorial of the EM Algorithm
and its Application to Parameter
Estimation for Gaussian Mixture and
Hidden Markov Models Platform: |
Size: 88064 |
Author:asif |
Hits:
Description: 基于隐马尔可夫模型的语音单字识别研究：本文针对线性模型在语音识别中的不足, 进行了隐马尔可夫模型(HMM)在
语音单字识别中的研究,主要对观察输出概率求解、 最佳状态序列寻找、 参数估计和
模型参数的选择进行了探讨.-Based on hidden Markov model speech word recognition: the lack of the linear model in speech recognition, hidden Markov model (HMM) speech word recognition, mainly on the observation of the output probability for solving the most best state sequence search, the choice of the parameter estimation and model parameters are discussed. Platform: |
Size: 198656 |
Author:郭粉玉 |
Hits:
Description: 一篇关于EM算法与MCMC算法的介绍与区别的论文。-EM VS MCMC for estimation of hidden markov modesl: A computational perspective. Copyright by Tobias Ryden Platform: |
Size: 959488 |
Author:夏茉儿 |
Hits:
Description: 常用的图像去噪算法，基于隐马尔可夫树模型的小波去噪 基于尺度空间和context模型相结合的自适应小波去噪 基于尺度和空间混合模型的小波图像去噪 Bayes估计阈值软门限去噪 -The denoising algorithm used in image denoising, wavelet hidden Markov tree model based on adaptive wavelet denoising combining the scale space and context model based on wavelet denoising image scale and spatial mixed model based on Bayes estimation soft threshold denoising Platform: |
Size: 117760 |
Author:jingxisikai |
Hits:
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