这样，就建立的社会通信的隐马尔可夫模型。
We use hidden Markov Model to simulate Externally-Connected hidden groups.
本文基于隐马尔可夫模型进行图像识别问题的研究。
This paper focuses on the research of image recognition based on the hidden Markov model.
提出了一种基于隐马尔可夫模型的文本信息抽取算法。
A new algorithm based on hidden Markov Model is proposed for text information extraction.
HTK：这是一个用于构建和操纵隐马尔可夫模型的便携式工具包。
HTK: Delve into this portable toolkit for building and manipulating hidden Markov models.
对隐马尔可夫模型训练过程中参数B的优化方法进行改进。
Improve on optimized method of parameter B in the process of HMM training.
隐马尔可夫模型参数通过期望最大化算法(EM)来估计。
这是一个笔者撰写改进了别人的隐马尔可夫模型算法的程序。
This is a writer writing improvement of the people's hidden Markov model algorithm procedures.
最后，采用隐马尔可夫模型（HMM）对分割结果进行识别。
Temporal segmentation results are recognized by HMM finally.
隐马尔可夫模型正在被愈来愈多地引入到生物医学信号的处理中。
Hidden Markov Model is now being applied increasingly in biomedical signal processing.
本论文采用隐马尔可夫模型(HMM)来减小解码与解调选择错误。
Decreases decoder and demodulator selection error using a Hidden-Markov Model (HMM) in this paper.
本文介绍多码本离散隐马尔可夫模型用于含噪声语音识别的研究成果。
A discrete hidden Markov model based on the multiple vector quantization codebooks is used here for speaker-dependent discrete speech recognition in Noisy Environments.
本文提出了将三阶隐马尔可夫模型运用到维吾尔语词性标注中的方法。
This paper describes a method of Uigur part-of-speech tagging with third-order Hidden Markov Model.
通过迭代学习的方法在大样本下进一步训练这些隐马尔可夫模型参数；
The HMMs' parameters are further trained by the method of iterative learning from a large data set;
提出一种隐马尔可夫模型和K -均值聚类混合模型的声目标识别方法。
A recognition method based on HMM and K-means cluster is proposed through extracting LPC characteristic from acoustic target.
提出了一种平行子状态隐马尔可夫模型用作噪声鲁棒语音识别的声学模型。
In this paper, a parallel sub-state hidden Markov model, which integrates the clean speech and noise information, and each state of the model has several parallel sub-states, is presented.
文章提出了一种基于多重隐马尔可夫模型和区域投影变换的手写体汉字识别新方法。
A new approach for handwritten Chinese character recognition based on multiple hidden Markov model classifiers and sub-region projection transform is proposed in the thesis.
基于连续隐马尔可夫模型(CHMM)框架的非特定人关键词识别基线系统的构建。
A baseline system of keyword spotting based on Continue Hidden Markov Model (CHMM) is constructed.
该文提出了基于隐马尔可夫模型局部最优状态路径的数据重建(LOPDI)算法。
This paper presents a HMM Local Optimal state Path-based Data Imputation (LOPDI) algorithm.
针对训练数据来源的多样化，提出了基于多模板隐马尔可夫模型的文本信息抽取算法。
This paper proposes a new algorithm using hidden Markov model for information extraction based on multiple templates due to the variety of training data.
介绍了一种基于振动信号隐马尔可夫模型(HMM)的新的齿轮故障检测和诊断方案。
A new gear fault detection and diagnosis scheme based on Hidden Markov Model (HMM) of vibration signals is introduced.
最后在实验部分对改进的平滑算法以及改进的隐马尔可夫模型做了相对原算法的对比实验。
At last the experiment of the improved smoothing algorithm and improved HMM between traditional algorithms shows the amelioration of new system.
提出了一种利用隐马尔可夫模型(HMM)和支持向量机(SVM)的两级指纹分类新方法。
A new two-stage method of fingerprint classification is proposed that is based on hidden Markov model (HMM) and support vector machine (SVM).
人脸识别方面，本文对在人脸识别中广泛应用的隐马尔可夫模型(HMM)的原理进行了介绍。
A hidden Markov model method (HMM) is used to recognize face in our automated recognition system.
提出用散射点参数作为识别特征，用隐马尔可夫模型（HMM）作分类器的雷达目标识别方法。
We contribute to automatic target recognition (ATR) by a hidden Markov model (HMM) based classifier, with parameters of scattering centers.
然后研究了用于语音识别的两种方法：隐马尔可夫模型(HMM)和人工神经网络(ANN)。
And then, two methods of speech recognition are researched: Hidden Markov Mode1 (HMM) and Artificial Neutral Net (ANN).
研究了2维隐马尔可夫模型的三个基本问题，包括概率评估问题、最优状态问题和参数估计问题。
The three basic problems of two-dimensional (2-d) hidden Markov models (HMMs) are studied, including probability evaluation, optimal states and parameter estimation.
提出了一种隐马尔可夫模型（HMM）和径向基函数神经网络（RBF）相结合的语音识别新方法。
Presents a new hybrid framework of hidden Markov models (HMM) and radial basis function (RBF) neural networks for speech recognition.
提出了一种隐马尔可夫模型（HMM）和径向基函数神经网络（RBF）相结合的语音识别新方法。
Presents a new hybrid framework of hidden Markov models (HMM) and radial basis function (RBF) neural networks for speech recognition.
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