广义高斯—马尔可夫模型是平差理论的一般模型。
The Generalized Gauss-Markoff model is the mast general form of adjustment model.
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.
本文运用灰色马尔可夫模型对路面破损状况进行预测。
This paper took the prediction of pavement condition index by the grey Markov model.
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.
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.
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.
讨论了应用马尔可夫模型方法分析容错导航系统可靠性的化简问题。
This paper deals with the simplification of reliability evaluation of Markov process for fault tolerant navigation system.
这说明运用马尔可夫模型进行河径流量的丰枯状态预报是有效可行的。
So, it is practical to use the sequential clustering and Markov model to forecast the river runoff .
本文提出了一种基于半马尔可夫模型的VHF信道访问协议分析方法。
A new method of VHF channel access protocol analysis based on semi-Markov model is presented in this paper.
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.
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.
建立马尔可夫模型并由马尔可夫状态转移概率矩阵计算出程序的可靠度。
We also present how to compute the reliability of a program based on factoring method and Markov model.
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.
动态故障树分析方法综合了故障树分析方法和马尔可夫模型两者的优点。
Dynamic fault tree combines the advantages of both fault tree and Markov model.
动态故障树分析方法综合了传统故障树分析方法和马尔可夫模型两者的优点。
Dynamic fault tree exploits the relative advantages of both fault tree and Markov model.
条件随机场是一种无向图模型，它具有产生式模型和最大熵马尔可夫模型的优点。
Conditional Random Fields (CRF) is arbitrary undirected graphical model that bring together the best of generative models and Maximum Entropy Markov models (MEMM).
其次，我们基于隐藏式马尔可夫模型与影像讯号提出了一个新的通道衰落预测方法。
Secondly, we propose a new method based on hidden Markov models and video images to predict channel fading.
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.
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.
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.
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).
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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