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Hidden Markov Models (HMM) have been used with
some success in recognizing printed Arabic words. In this
paper, a complete scheme for totally unconstrained
Arabic handwritten word recognition based on a Model
discriminant HMM is presented. A
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了解隐马尔科夫模型HMM的概念、组成和需要解决的问题；掌握三个基本算法：forward算法、Viterbi算法和Baum-Welch算法，并利用matlab进行实验分析一道具体问题-Understand the concept of Hidden Markov Model HMM, composition and problems to be solved mastered three basic algorithms: forward algorithm, Viterbi algorithm
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用Viterbi算法来解码隐马尔科夫模型(HMM)的状态变量。其中，mainfile_Vit.m是主函数，Viterbi_algorithm.m是调用的Viterbi算法函数。-Viterbi algorithm for decoding the hidden states of the Hidden Markov Model(HMM). In this folder, "mainfile_Vit.m" file is the main function, and "Viterbi_algori
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An Introduction to HMM-Based (hidden Markov model)
Speech Synthesis
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HTK是英国剑桥大学开发的一套基于C语言的隐马尔科夫模型工具箱，主要应用于语音识别、语音合成的研究，也被用在其他领域，如字符识别和DNA排序等。HTK是重量级的HMM版本。-Cambridge University HTK is a C-based language developed by the Hidden Markov Model Toolkit, mainly used in speech recognition, speech synthesis research, has also
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基于隐马尔科夫模型HMM的行为识别matlab代码-Hidden Markov Model behavior recognition matlab code
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Abstract: Smartphone positioning is an enabling technology used to create new business
in the navigation and mobile location-based services (LBS) industries. This paper presents
a smartphone indoor positioning engine named HIPE that can be easily
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HMM code for Discrete Hidden Markov Model
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In this paper we present the necessary theory to
detect fraud in credit card transaction processing using a
Hidden Markov Model (HMM). An HMM is initially trained
with the normal behavior of a cardholder. If an incoming
credit card transaction is
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HTKbook 3.4
包括所有的HTK 语言的用法以及samples(HTK is a toolkit for building Hidden Markov Models (HMMs). HMMs can be used to model
any time series and the core of HTK is similarly general-purpose. However, HTK is primarily
designed for building HMM-based s
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The speech signal for the particular isolated word can be viewed as the one generated using the sequential generating probabilistic model known as hidden Markov
model (HMM). Consider there are n states in the HMM. The particular isolated
speech sig
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基于驾驶模拟器实验数据,结合高斯混合隐马尔可夫模型(GM-HMM),对高速公路的超车行为进行 辨 识 , 并 对 驾 驶 员 意 图 和 超 车 行 为 是 否 正 常 进 行 分 析 。 结 果 表 明 , 基 于 GM-HMM 的 辨 识 方 法 能 有 效 辨 识 多 种 驾 驶 工况下的不正常超车行 为 。(Based on driving simulator experiment data, combined with Gauss hybrid hidden Markov model
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