An Overview of Adaptive Sorting PDF Download
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Author: Alistair Moffat
Publisher:
ISBN:
Category :
Languages : en
Pages : 13
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Book Description
Author: Alistair Moffat
Publisher:
ISBN:
Category :
Languages : en
Pages : 13
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Book Description
Author: Vladimir Estivill-Castro
Publisher: London : Department of Computer Science, University of Western Ontario
ISBN: 9780771414312
Category :
Languages : en
Pages : 48
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Book Description
Author: Alistair Moffat
Publisher:
ISBN:
Category :
Languages : en
Pages : 10
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Book Description
Author: V. Estivill-Castro
Publisher:
ISBN:
Category :
Languages : en
Pages : 17
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Book Description
Author: Christos Levcopoulos
Publisher:
ISBN:
Category :
Languages : en
Pages : 8
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Book Description
Author: Estivill-Castro, Vladimir
Publisher: London, Ont. : Department of Computer Science, University of Western Ontario
ISBN: 9780771415258
Category :
Languages : en
Pages : 12
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Book Description
Author: Danny Weyns
Publisher: John Wiley & Sons
ISBN: 1119574935
Category : Technology & Engineering
Languages : en
Pages : 288
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Book Description
A concise and practical introduction to the foundations and engineering principles of self-adaptation Though it has recently gained significant momentum, the topic of self-adaptation remains largely under-addressed in academic and technical literature. This book changes that. Using a systematic and holistic approach, An Introduction to Self-adaptive Systems: A Contemporary Software Engineering Perspective provides readers with an accessible set of basic principles, engineering foundations, and applications of self-adaptation in software-intensive systems. It places self-adaptation in the context of techniques like uncertainty management, feedback control, online reasoning, and machine learning while acknowledging the growing consensus in the software engineering community that self-adaptation will be a crucial enabling feature in tackling the challenges of new, emerging, and future systems. The author combines cutting-edge technical research with basic principles and real-world insights to create a practical and strategically effective guide to self-adaptation. He includes features such as: An analysis of the foundational engineering principles and applications of self-adaptation in different domains, including the Internet-of-Things, cloud computing, and cyber-physical systems End-of-chapter exercises at four different levels of complexity and difficulty An accompanying author-hosted website with slides, selected exercises and solutions, models, and code Perfect for researchers, students, teachers, industry leaders, and practitioners in fields that directly or peripherally involve software engineering, as well as those in academia involved in a class on self-adaptivity, this book belongs on the shelves of anyone with an interest in the future of software and its engineering.
Author: Kutluyil Doğançay
Publisher: Academic Press
ISBN: 0080921159
Category : Technology & Engineering
Languages : en
Pages : 295
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Book Description
Partial-update adaptive signal processing algorithms not only permit significant complexity reduction in adaptive filter implementations, but can also improve adaptive filter performance in telecommunications applications. This book gives state-of-the-art methods for the design and development of partial-update adaptive signal processing algorithms for use in systems development.Partial-Update Adaptive Signal Processing provides a comprehensive coverage of key partial updating schemes, giving detailed information on the theory and applications of acoustic and network echo cancellation, channel equalization and multiuser detection. It also examines convergence and stability issues for partial update algorithms, providing detailed complexity analysis and a unifying treatment of partial-update techniques.Features:• Advanced analysis and design tools• Application examples illustrating the use of partial-update adaptive signal processing• MATLAB codes for developed algorithms This unique reference will be of interest to signal processing and communications engineers, researchers, R&D engineers and graduate students."This is a very systematic and methodical treatment of an adaptive signal processing topic, of particular significance in power limited applications such as in wireless communication systems and smart ad hoc sensor networks. I am very happy to have this book on my shelf, not to gather dust, but to be consulted and used in my own research and teaching activities" – Professor A. G. Constantinides, Imperial College, LondonAbout the author:Kutluyil Dogançay is an associate professor of Electrical Engineering at the University of South Australia. His research interests span statistical and adaptive signal processing and he serves as a consultant to defence and private industry. He was the Signal Processing and Communications Program Chair of IDC Conference 2007, and is currently chair of the IEEE South Australia Communications and Signal Processing Chapter. - Advanced analysis and design tools - Algorithm summaries in tabular format - Case studies illustrate the application of partial update adaptive signal processing
Author: Svante Carlsson
Publisher:
ISBN:
Category :
Languages : en
Pages : 8
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Book Description
Author: Feliz Nauman
Publisher: Morgan & Claypool Publishers
ISBN: 1608452212
Category : Technology & Engineering
Languages : en
Pages : 87
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Book Description
With the ever increasing volume of data, data quality problems abound. Multiple, yet different representations of the same real-world objects in data, duplicates, are one of the most intriguing data quality problems. The effects of such duplicates are detrimental; for instance, bank customers can obtain duplicate identities, inventory levels are monitored incorrectly, catalogs are mailed multiple times to the same household, etc. Automatically detecting duplicates is difficult: First, duplicate representations are usually not identical but slightly differ in their values. Second, in principle all pairs of records should be compared, which is infeasible for large volumes of data. This lecture examines closely the two main components to overcome these difficulties: (i) Similarity measures are used to automatically identify duplicates when comparing two records. Well-chosen similarity measures improve the effectiveness of duplicate detection. (ii) Algorithms are developed to perform on very large volumes of data in search for duplicates. Well-designed algorithms improve the efficiency of duplicate detection. Finally, we discuss methods to evaluate the success of duplicate detection. Table of Contents: Data Cleansing: Introduction and Motivation / Problem Definition / Similarity Functions / Duplicate Detection Algorithms / Evaluating Detection Success / Conclusion and Outlook / Bibliography
