Language : English
Published : 2018-02-28
Pages : 242
Interference Management in Wireless Networks: Fundamental Bounds and the Role of Cooperation
Learn about an information-theoretic approach to managing interference in future generation wireless networks. Focusing on cooperative schemes motivated by Coordinated Multi-Point (CoMP) technology, the book develops a robust theoretical framework for interference management that uses recent advancements in backhaul design, and practical pre-coding schemes based on local cooperation, to deliver the increased speed and reliability promised by interference alignment. Gain insight into how simple, zero-forcing pre-coding schemes are optimal in locally connected interference networks, and discover how significant rate gains can be obtained by making cell association decisions and allocating backhaul resources based on centralized (cloud) processing and knowledge of network topology. Providing a link between information-theoretic analyses and interference management schemes that are easy to implement, this is an invaluable resource for researchers, graduate students and practicing engineers in wireless communications.
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The world of data warehousing has changed remarkably since the first edition of The Data Warehouse Lifecycle Toolkit was published in 1998. With this new edition, Ralph Kimball and his colleagues have refined the original set of Lifecycle methods and techniques based on their consulting and training experience. They walk you through the detailed steps of designing, developing, and deploying a data warehousing/business intelligence system. With substantial new and updated content, this second edition again sets the standard in data warehousing for the next decade.
About the Author
The authors’ professional careers have followed remarkably similar paths. Each author has focused on data warehousing and business intelligence (DW/BI) consulting and education for more than fifteen years. Most worked together at Metaphor Computer Systems, a pioneering decision support vendor, in the 1980s. All the authors are members of the Kimball Group and teach for KimballUniversity. They contribute regularly to Intelligent Enterprise magazine and other industry publications; most have previously written books in the Toolkit series. Ralph Kimball founded the Kimball Group. Since the mid 1980s, he has been the DW/BI industry’s thought leader on the dimensional approach and trained more than 10,000 IT professionals. Ralph has his Ph.D. in Electrical Engineering from Stanford University. Margy Ross is President of the Kimball Group. She has focused exclusively on DW/BI since 1982 with an emphasis on business requirements analysis and dimensional modeling. Margy graduated with a BS in Industrial Engineering from Northwestern University. Warren Thornthwaite began his DW/BI career in 1980. After managing Metaphor’s consulting organization, he worked for Stanford University and WebTV. Warren holds a BAin Communications Studies from the University of Michigan and anMBA from the University of Pennsylvania’sWharton School. JoyMundy has focused onDW/BIsystems since 1992 with stints at Stanford, Web TV, and Microsoft’s SQL Server product development organization. Joy graduated from Tufts University with a BA in Economics, and from Stanford University with an MS in Engineering Economic Systems. Bob Becker has helped clients across a variety of industries with their DW/BI challenges and solutions since 1989, including extensive work with health care organizations. Bob has a BSB in Marketing from the University of Minnesota’s School of Business.
Evolutionary computation, the use of evolutionary systems as computational processes for solving complex problems, is a tool used by computer scientists and engineers who want to harness the power of evolution to build useful new artifacts, by biologists interested in developing and testing better models of natural evolutionary systems, and by artificial life scientists for designing and implementing new artificial evolutionary worlds. In this clear and comprehensive introduction to the field, Kenneth De Jong presents an integrated view of the state of the art in evolutionary computation. Although other books have described such particular areas of the field as genetic algorithms, genetic programming, evolution strategies, and evolutionary programming, Evolutionary Computation is noteworthy for considering these systems as specific instances of a more general class of evolutionary algorithms. This useful overview of a fragmented field is suitable for classroom use or as a reference for computer scientists and engineers.
About the Author
Nicole Fenton is an independent writer and editor in Brooklyn. She has worked at a large social network, a startup incubator, a design studio, and Apple. She manages content projects of all sizes and teaches writing as a design practice. Kate Kiefer Lee is a writer and editor at MailChimp and a former magazine editor. She has written for publications like Forbes and A List Apart, and spoken about web content around the world. She teaches people how to write like they talk.
This book covers the field of machine learning, which is the study of algorithms that allow computer programs to automatically improve through experience. The book is intended to support upper level undergraduate and introductory level graduate courses in machine learning.