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Shankar Sastry is Dean of the College of Engineering, Professor of Electrical Engineering and Computer Science and Professor of Bioengineering at the University of California, Berkeley.
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This textbook explores the different aspects of data mining from the fundamentals to the complex data types and their applications, capturing the wide diversity of problem domains for data mining issues.
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Many industry experts consider unsupervised learning the next frontier in artificial... Læs mere
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This self-contained textbook introduces all the relevant mathematical concepts needed to understand and use machine learning methods, with a minimum of prerequisites.... Læs mere
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A comprehensive overview of high-performance pattern recognition techniques and approaches to Computational Molecular Biology This book surveys the developments of techniques and approaches on pattern recognition related to Computational Molecular Biology.
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While the deployment of large-scale biometric systems in both commercial and government applications has increased the public awareness of this technology, "Introduction to... Læs mere
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Provides an approach to pattern recognition in which objects are characterized by relations to other objects instead of by using features or models. This book is intended for researchers and systems designers studying or developing pattern recognition systems.
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Contains a series of ICAPR proceedings on the advances of different facets of pattern recognition. This work tackles open... Læs mere
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Speech coding has evolved into a highly matured branch of signal processing, with deployment of a plethora of products such as cellular phones, answering machines, communication devices, and more recently, voice over internet protocol (VoIP).
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Statistical pattern recognition relates to the use of statistical techniques for analysing data measurements in order to extract information and make justified decisions. It is a very active area of study and research, which has seen many advances in recent years.
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