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"Academic Press Library in Signal Processing, Volume 7: Array, Radar and Communications Engineering is aimed at university researchers, post graduate students and R&D engineers in the industry, providing a tutorial-based, comprehensive review of key topics and technologies of research in Array and Radar Processing, Communications Engineering and Machine Learning. Users will find the book to be an invaluable starting point to their research and initiatives. With this reference, readers will quickly grasp an unfamiliar area of research, understand the underlying principles of a topic, learn how a topic relates to other areas, and learn of research issues yet to be resolved."--

Signal processing. --- Processing, Signal --- Information measurement --- Signal theory (Telecommunication)

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Academic Press Library in Signal Processing, Volume 6: Image and Video Processing and Analysis and Computer Vision is aimed at university researchers, post graduate students and R&D engineers in the industry, providing a tutorial-based, comprehensive review of key topics and technologies of research in both image and video processing and analysis and computer vision. The book provides an invaluable starting point to the area through the insight and understanding that it provides. With this reference, readers will quickly grasp an unfamiliar area of research, understand the underlying principles of a topic, learn how a topic relates to other areas, and learn of research issues yet to be resolved.

Artificial intelligence. Robotics. Simulation. Graphics

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A classic -- offering comprehensive and unified coverage with a balance between theory and practice! Pattern recognition is integral to a wide spectrum of scientific disciplines and technologies including image analysis, speech recognition, audio classification, communications, computer-aided diagnosis, and data mining. The authors, leading experts in the field of pattern recognition, have once again provided an up-to-date, self-contained volume encapsulating this wide spectrum of information. Each chapter is designed to begin with basics of theory progressing to advanced topics and then discusses cutting-edge techniques. Problems and exercises are present at the end of each chapter with a solutions manual provided via a companion website where a number of demonstrations are also available to aid the reader in gaining practical experience with the theories and associated algorithms. This edition includes discussion of Bayesian classification, Bayesian networks, linear and nonlinear classifier design (including neural networks and support vector machines), dynamic programming and hidden Markov models for sequential data, feature generation (including wavelets, principal component analysis, independent component analysis and fractals), feature selection techniques, basic concepts from learning theory, and clustering concepts and algorithms. This book considers classical and current theory and practice, of both supervised and unsupervised pattern recognition, to build a complete background for professionals and students of engineering. FOR INSTRUCTORS: To obtain access to the solutions manual for this title simply register on our textbook website (textbooks.elsevier.com)and request access to the Computer Science or Electronics and Electrical Engineering subject area. Once approved (usually within one business day) you will be able to access all of the instructor-only materials through the "Instructor Manual" link on this book's full web page. * The latest results on support vector machines including v-SVM's and their geometric interpretation * Classifier combinations including the Boosting approach * State-of-the-art material for clustering algorithms tailored for large data sets and/or high dimensional data, as required by applications such as web-mining and bioinformatics * Coverage of diverse applications such as image analysis, optical character recognition, channel equalization, speech recognition and audio classification.

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An accompanying manual to Theodoridis/Koutroumbas, Pattern Recognition, that includes Matlab code of the most common methods and algorithms in the book, together with a descriptive summary and solved examples, and including real-life data sets in imaging and audio recognition.

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This third volume of a four volume set, edited and authored by world leading experts, gives a review of the principles, methods and techniques of important and emerging research topics and technologies in array and statistical signal processing. With this reference source you will: Quickly grasp a new area of research Understand the underlying principles of a topic and its applicationAscertain how a topic relates to other areas and learn of the research issues yet to be resolvedQuick tutori

Signal processing. --- Processing, Signal --- Information measurement --- Signal theory (Telecommunication)