Practical Optimization: Algorithms and Engineering Applications - Rilegato

Antoniou, Andreas; Lu, Wu-Sheng

Rilegato

ISBN 10: 107160841X ISBN 13: 9781071608418

Casa editrice: Springer-Nature New York Inc, 2021

Riassunto

This textbook provides a hands-on treatment of the subject of optimization. A comprehensive set of problems and exercises makes it suitable for use in one or two semesters of an advanced undergraduate course or a first-year graduate course. Each half of the book contains a full semester’s worth of complementary yet stand-alone material. The practical orientation of the topics chosen and a wealth of useful examples also make the book suitable as a reference work for practitioners in the field.

In this second edition the authors have added sections on recent innovations, techniques, and methodologies.

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Informazioni sull?autore

Prof. Andreas Antoniou received his Ph.D. in Electrical Engineering from the University of London in 1966 and is a Fellow of the IET and IEEE. He served as the founding Chair of the Dept. of Electrical and Computer Engineering at the University of Victoria, Canada, and is now Professor Emeritus in the same department. He is the author of Digital Filters: Analysis, Design, and Applications (McGraw-Hill, 1993) and Digital Signal Processing: Signals, Systems, and Filters (McGraw-Hill, 2005). He served as Associate Editor/Editor of IEEE Trans. on Circuits and Systems from June 1983 to May 1987, as a Distinguished Lecturer of the IEEE Signal Processing Society in 2003, as General Chair of the 2004 Intl. Symp. on Circuits and Systems, and is currently serving as a Distinguished Lecturer of the IEEE Circuits and Systems Society. He received the Ambrose Fleming Premium for 1964 from the IEEE (best paper award), the CAS Golden Jubilee Medal from the IEEE Circuits and Systems Society, the B.C. Science Council Chairman’s Award for Career Achievement for 2000, a Doctor Honoris Causa from the Metsovio National Technical University of Athens, Greece, n 2002, and the IEEE Circuits and Systems Society 2005 Technical Achievement Award.

Prof. Wu-Sheng Lu received his B.S. degree in Mathematics from Fudan University, Shanghai, China in 1964, an M.E. degree in Automation from the East China Normal University, Shanghai in 1981, and an M.S. degree in Electrical Engineering and his Ph.D. in Control Science from the University of Minnesota, Minneapolis, n 1983 and 1984, respectively. He was a postdoctoral fellow at the University of Victoria, Canada in 1985 and a visiting Asst. Professor with the University of Minnesota in 1986. Since 1987 he has been with the University of Victoria where he is a full professor. His current teaching and research interests are digital signal processing and the application of optimization methods. He is the coauthor with Prof. Antoniou of Two-Dimensional Digital Filters (Marcel Dekker, 1992). He served as an Associate Editor of the Canadian Journal of Electrical and Computer Engineering in 1989, and Editor of the same journal from 1990 to 1992. He served as an Associate Editor for the IEEE Trans. on Circuits and Systems, Part II, from 1993 to 1995 and for Part I of the same journal from 1999 to 2001 and from 2004 to 2005. Presently he is serving as Associate Editor for the Intl. J. of Multidimensional Systems and Signal Processing. He is a Fellow of the Engineering Institute of Canada and the IEEE.

Dalla quarta di copertina

In recent decades, advancements in the efficiency of digital computers and the evolution of reliable software for numerical computation have led to a rapid growth in the theory, methods, and algorithms of numerical optimization. This body of knowledge has motivated widespread applications of optimization methods in many disciplines (e.g., engineering, business, and science) and has subsequently led to problem solutions that were considered intractable not long ago.

This unique and comprehensive textbook provides an extensive and practical treatment of the subject of optimization. Each half of the book contains a full semester’s worth of complementary, yet stand-alone material. In this substantially enhanced second edition, the authors have added sections on recent innovations, techniques, methodologies, and many problems and examples. These features make the book suitable for use in one or two semesters of a first-year graduate course or an advanced undergraduate course.

Key features:

• proven and extensively class-tested content
• presents a unified treatment of unconstrained and constrained optimization, making it a dual-use textbook
• introduces new material on convex programming, sequential quadratic programming, alternating direction methods of multipliers (ADMM), and convex-concave procedures
• includes methods such as semi-definite and second-order cone programming 
• adds new material to state-of-the-art applications for both unconstrained and constrained optimization
• provides a complete teaching package with many MATLAB examples and online solutions to the end-of-chapter problems
• uses a practical and accessible treatment of optimization 
• provides two appendices that cover background theory so that non-experts can understand the underlying theory

With its strong and practical treatment of optimization, this significantly enhanced revision of a classic textbook will be indispensable to the learning of university and college students and will also serve as a useful reference volume for scientists and industry professionals.

Andreas Antoniou is Professor Emeritus in the Dept. of Electrical and Computer Engineering at the University of Victoria, Canada. Wu-Sheng Lu is Professor in the same department and university.

Dettagli dell'edizione

• Editore: Springer-Nature New York Inc
• Data di pubblicazione: 2021
• Lingua: Inglese
• ISBN 10: 107160841X
• ISBN 13: 9781071608418
• Rilegatura: Copertina rigida
• Numero edizione: 2
• Numero di pagine: 721
• Contatto del produttore: non disponibile
• Persona responsabile: CMN Printpool Inh. Mathis Neumann; https://www.also.com/ec/cms5/en_6000/6000/index.jsp; ; Friedrich-Karl-Str. 9; Hamburg; Germania