文件名称：模式识别中的马尔可夫模型
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更新时间：2011-04-09 18:38:40
模型 模式识别 马尔可夫
The development of pattern recognition methods on the basis of so-called Markov models is tightly coupled to the technological progress in the field of automatic speech recognition. Today, however, Markov chain and hidden Markov models are also applied in many other fields where the task is the modeling and analysis of chronologically organized data, for example genetic sequences or handwritten texts. Nevertheless, in monographs, Markov models are almost exclusively treated in the context of automatic speech recognition and not as a general, widely applicable tool of statistical pattern recognition. In contrast, this book puts the formalism of Markov chain and hidden Markov models at the center of its considerations.With the example of the three main application areas of this technology—namely automatic speech recognition, handwriting recognition, and the analysis of genetic sequences— this book demonstrates which adjustments to the respective application area are necessary and how these are realized in current pattern recognition systems. Besides the treatment of the theoretical foundations of the modeling, this book puts special emphasis on the presentation of algorithmic solutions, which are indispensable for the successful practical application of Markov model technology. Therefore, it addresses researchers and practitioners from the field of pattern recognition as well as graduate students with an appropriate major field of study, who want to devote themselves to speech or handwriting recognition, bioinformatics, or related problems and want to gain a deeper understanding of the application of statistical methods in these areas. The origins of this book lie in the author’s extensive research and development in the field of statistical pattern recognition, which initially led to a German book published by Teubner,Wiesbaden, in 2003. The present edition is basically a translation of the German version with several updates and modifications addressing an international audience. This book would not have been possible without the encouragement and support of my colleague Thomas Pl¨otz, University of Dortmund, Germany, whom I would like to cordially thank for his efforts.