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- This paper presents a hybrid model of Continuous Density Hidden Markov Model (CDHMM) and the Multi-Layer Perceptron (MLP). 本文提出了一种由连续隐马尔可夫模型（CDHMM）与多层感知器（MLP）构成的混合模型，并将该模型应用于语音孤立词识别。
- A new synthetic aperture radar (SAR) image filter method is proposed based on hidden Markov model (HMM). 在小波域隐Markov模型(HMM)的基础上提出一种新的合成孔径雷达(SAR)图像的滤波方法。
- This paper proposes a novel contour tracking algorithm based on Hidden Markov Model (HMM) and optic flow. 提出了一个新颖的基于隐马尔科夫模型与光流的轮廓线跟踪算法。
- In this thesis, we use both Hidden Markov Model (HMM) and Weight Array Model (WAM) to predict the splice sites. 本文基于隐Markov模型(HMM)和权重阵列模型(WAM)两种方法来预测剪接位点。
- It produces Mongolian translation from the single language material through use of dictionary-based model and Hidden Markov Model. 基于HMM模型的蒙古文生成方法采用词典驱动模型和HMM模型从单语料生成蒙古文译文。
- The strong limit theorem of hidden nonhomogeneous Markov model is studied when the hidden chains are nonhomogeneous Markov chains. 摘要假定隐藏的马尔可夫链为非齐次，研究隐非齐次马尔可夫模型的一些强极限定理。
- As corollaries, several strong limit theorems about occurred frequency of states for hidden nonhomogeneous Markov model are obtained. 作为定理的推论，得到了隐非齐次马尔可夫模型状态出现频率的一类强极限定理。
- Second, we discuss the three base question of Hidden Markov Model, induce two new algorithms, named mend Baum-Welch and mend Viterbi. 其次，本文在研究了隐马尔可夫模型的基础上，对其三个基本问题进行了比较细致的论证，并引入改进Viterbi算法。
- The continuous density hidden Markov model(CDHMM) is adopted, Viterbi and Baum-Welch reestimation algorithms is utilized to train and recognize the speech signals. 采用连续HMM模型，利用Baum-Welth重估、Viterbi算法进行训练和识别，实现系统软件设计。
- This paper presents a Chinese named entity recognition system that integrates the Hidden Markov Model (HMM) and rules which are automatic extracted from the training corpus. 本文实现的中文命名实体识别系统采用了隐马尔可夫模型(Hidden Markov Model,HMM)与自动规则提取相结合的方法。
- Then sub-state maximum likelihood and combining transition sub-state maximum likelihood (CTSSML) for parellel sub-state hidden Markov model are also presented. 在此基础上，提出了两种用于平行子状态隐马尔可夫模型的识别解码策略-子状态最大似然解码和联合转移子状态最大似然解码。
- The substance of this magisterial thesis is the research and improvement of speaker recognition which is based on the VQ (Vector Quantization) and HMM (Hidden Markov Model). 本论文主要内容是基于矢量量化(VQ) 和隐马尔可夫模型（HMM）的说话人识别算法的研究和改进。
- Proposes a hybrid approach for phoneme recognition based on combination of improved counter-propagation (CP) neural network and hidden Markov model (HMM). 提出了一种基于改进对偶传播 (CP) 神经网络与隐马尔可夫模型 (HMM) 相结合的混合音素识别方法。
- Through the combination of Hidden Markov Model POS tagging and the smoothing algorithm, we obtain a tagging precision of 86%, and a disambiguation of 82%. 在实现基于隐马尔可夫模型的词性标注同时，结合平滑算法，标注正确率达到86%25，排歧正确率达到82%25；
- This paper presents a discrete Markov model for analyzing the PFD(avg). 该文提出了一种采用离散Markov模型定量计算PFD(avg)的有效方法。
- CONCLUSIONS:Markov model should be applied in drug market extensively. 结论:马尔科夫模型应在药品经济领域得到推广应用。
- Hidden Markov Models are introduced to the area of ship-radiated noise recognition. 将隐马尔可夫模型引入到舰船噪声目标识别中。
- It used Markov modeler to model and forecast spatial series. 使用马尔可夫模型对读请求的空间特征进行建模、预测。
- By hidden Markov model, it combined with a prior segmentation model which is independent to noise feature as the compensation for the mismatch of acoustic model to enhance the robust performance. 然后,假设音节长度序列符合一阶马尔科夫过程,经过归一化处理后,求出了切分的先验概率公式,得到了贝叶斯方法的切分模型。
- In this paper a method of continuous speech recognition based on hidden Markov models (HMM) and vector quantization (VQ) is discussed. 本文讨论基于隐马尔可夫模型(HMM)和矢量量化(VQ)的连续语音识别方法。
