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Markov Models for Pattern Recognition : From Theory to Applications

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Cover of 'Markov Models for Pattern Recognition : From Theory to Applications'

Table of Contents

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    Book Overview
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    Chapter 1 Introduction
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    Chapter 2 Application Areas
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    Chapter 3 Foundations of Mathematical Statistics
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    Chapter 4 Vector Quantization and Mixture Estimation
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    Chapter 5 Hidden Markov Models
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    Chapter 6 n -Gram Models
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    Chapter 7 Computations with Probabilities
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    Chapter 8 Configuration of Hidden Markov Models
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    Chapter 9 Robust Parameter Estimation
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    Chapter 10 Efficient Model Evaluation
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    Chapter 11 Model Adaptation
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    Chapter 12 Integrated Search Methods
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    Chapter 13 Speech Recognition
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    Chapter 14 Handwriting Recognition
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    Chapter 15 Analysis of Biological Sequences
Attention for Chapter 4: Vector Quantization and Mixture Estimation
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