当前位置:
首页
资源下载
![](/images/right.gif)
搜索资源 - HMM Hidden Markov Model
搜索资源列表
-
0下载:
This code implements in C++ a basic left-right hidden Markov model
and corresponding Baum-Welch (ML) training algorithm. It is meant as
an example of the HMM algorithms described by L.Rabiner (1) and
others. Serious students are directed to the
-
-
0下载:
Hidden_Markov_model_for_automatic_speech_recognition
This code implements in C++ a basic left-right hidden Markov model
and corresponding Baum-Welch (ML) training algorithm. It is meant as
an example of the HMM algorithms described by L.Rabiner
-
-
0下载:
基于隐而马可夫的连续语音识别中声学模型的建立及其实现-Based on Hidden Markov and continuous speech recognition acoustic model and its realization
-
-
0下载:
多尺度变换域隐马尔可夫模型能够有效地描述变换域系数在尺度间、尺度内和方向间的统计相关性,是
一种新的统计图像感知与识别方法. 文中以变换域系数的统计相关性描述为中心,以模型的设计和应用的开展为
两翼,深入分析了子波变换的三级统计特性与机理,比较研究了多尺度变换域的十种统计模型,并系统评述了这些
模型在图像感知、处理和分析中的最新进展. 同时,具体论述了这一领域研究中两类成功的实例:图像去噪和图像
纹理分割. 对于前者,以Lena 图像为测试用例分析比较了以变换域统计模型为核心的
-
-
0下载:
real-time 3D pointing gesture
recognition algorithm for natural human-robot interaction
(HRI). The recognition errors in previous pointing gesture
recognition algorithms are mainly caused by the low performance
of the hands tracking module an
-
-
0下载:
维特比算法
寻找最可能的隐藏状态序列(Finding most probable sequence of hidden states)
对于一个特殊的隐马尔科夫模型(HMM)及一个相应的观察序列,我们常常希望能找到生成此序列最可能的隐藏状态序列。
-Viterbi algorithm to find the most likely hidden state sequence (Finding most probable sequence of hidden states) for a
-
-
0下载:
HMM model- hidden markov model descr iption algorithm
-
-
0下载:
基于双重随机性的隐马尔科夫模型(Hide MarKov Model)的C语言实现-Based on double random hidden Markov model (HMM) of the C language
-
-
0下载:
matlab implementation for forward-backward algorithm for train and test of hidden markov model (HMM).
-
-
0下载:
就目前三种主流的语音识别算法:动态时间规(DTW)、隐马尔科夫模型(HMM)和人工神经网络(ANN)。分析它们的原理、特点及实现过程,对 DTW 的语音识别进行实验,通过对比分析三种算法的特点,结合本文研究的实际情况,选择 DTW 作为研究的重点,提出利用遗传算法对其进行改进。
-The three mainstream speech recognition algorithms: Dynamic Time Regulations (DTW), hidden Markov model (HM
-
-
0下载:
HMM是隐马氏模型,预测蛋白质的二级结构,当你输入一段未知的需要测定的蛋白质序列时,利用已经训练好的蛋白质,可以预测蛋白质的二级结构
-HMM is a hidden Markov model, the predicted secondary structure of the protein, when you enter a need to determine the unknown protein sequence, the use of has trained proteins, th
-
-
0下载:
此工具箱支持推理和学习HMM模型,拥有的算法有离散输出(DHMM),高斯输出(GHMM),或其混合物的高斯输出(mhmm)。-Hidden Markov Model (HMM) Toolbox for Matlab,This toolbox supports inference and learning for HMMs with discrete outputs (dhmm s), Gaussian outputs (ghmm s), or mixtures of Gaussians outp
-
-
0下载:
隐马尔科夫编程。Jahmm (pronounced “jam”), is a Java implementation of Hidden Markov Model (HMM) related algorithms. It’s been designed to be easy to use (e.g. simple things are simple to program) and general purpose.-Hidden Markov programming.Jahmm (pronounc
-
-
0下载:
关于隐马尔可夫模型HMM三个问题的实现,用c++实现,是初学者学习的好资料-Hidden Markov Model HMM three realization c++ of realization is good for beginners to learn
-
-
0下载:
语音信号处理 包括语音信号的同态处理和先行预测编码分析(LPC) 隐马尔可夫模型的分析(HMM)等-The voice signal processing includes a voice signal the homomorphic processing and the first prediction coding analysis (LPC) analysis of the Hidden Markov Model (HMM)
-
-
0下载:
Fox & Pigeon Laboratory 发布一款基于隐马尔可夫模型的英语语音合成软件(HMM based English Text-To-Speech, TTS):FoxPigeonTTS alpha版。
近年来,基于HMM的语音合成系统得到广泛的重视和应用。我们实验室实现的基于HMM的语音合成系统基本不需要任何语言学知识指导系统训练,构建时间短,构建过程基本不需要人工干预,而由于系统属于参数化合成方法,系统的合成结果灵活多变,可以很容易的应用于多个发音人,多种发音风格,多种
-
-
0下载:
隐马尔科夫模型是语音识别中的重要算法思想,这里在matlab下实现了一个原理性的算法-Hidden markov models is an important algorithm in speech recognition, here under the matlab implements a rational algorithm
-
-
0下载:
了解隐马尔科夫模型HMM的概念、组成和需要解决的问题;通过matlab分析和三个基本算法分析读研和就业问题:forward算法、Viterbi算法和Baum-Welch算法-Understand the concept of Hidden Markov Model HMM, composition and problems to be solved matlab analysis by three basic algorithms: forward algorithm, Viterbi alg
-
-
0下载:
在VC6.0平台上进行编写的,包括隐马尔科夫模型(HMM)和混合高斯模型(GMM)在内的用于模板训练的算法。(The algorithm for template training is written on VC6.0 platform, including hidden Markov model (HMM) and mixed Gauss model (GMM).)
-
-
1下载:
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
-