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Efficiency and Scalability Methods for Computational Intellect

Efficiency and Scalability Methods for Computational Intellect

Boris Igelnik, Jacek M. Zurada
Copyright: © 2013 |Pages: 370
ISBN13: 9781466639423|ISBN10: 1466639423|EISBN13: 9781466639430
DOI: 10.4018/978-1-4666-3942-3
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MLA

Igelnik, Boris, and Jacek M. Zurada, editors. Efficiency and Scalability Methods for Computational Intellect. IGI Global, 2013. https://doi.org/10.4018/978-1-4666-3942-3

APA

Igelnik, B. & Zurada, J. M. (Eds.). (2013). Efficiency and Scalability Methods for Computational Intellect. IGI Global. https://doi.org/10.4018/978-1-4666-3942-3

Chicago

Igelnik, Boris, and Jacek M. Zurada, eds. Efficiency and Scalability Methods for Computational Intellect. Hershey, PA: IGI Global, 2013. https://doi.org/10.4018/978-1-4666-3942-3

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Computational modeling and simulation has developed and expanded into a diverse range of fields such as digital signal processing, image processing, robotics, systems biology, and many more; enhancing the need for a diversifying problem solving applications in this area.

Efficiency and Scalability Methods for Computational Intellect presents various theories and methods for approaching the problem of modeling and simulating intellect in order to target computation efficiency and scalability of proposed methods. Researchers, instructors, and graduate students will benefit from this current research and will in turn be able to apply the knowledge in an effective manner to gain an understanding of how to improve this field.

Table of Contents

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Front Materials
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Title Page
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Copyright Page
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Editorial Advisory Board
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Foreword
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Preface
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Chapters
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Efficient and Scalable Methods in Machine Learning, Data Mining, and Medicine
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Efficient and Scalable Methods in Image Processing, Robotics, Control, Computer Networks Defense, Human Identification, and Combinatorial Optimization
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Chapter 3
Concepts  (pages 218-218)
Concepts
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Back Materials
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Compilation of References
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About the Contributors
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Index
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