Digital Signal Processing and Spectral Analysis for Scientists

Concepts and Applications

Nonfiction, Science & Nature, Science, Physics, Mathematical Physics, Technology, Electronics
Cover of the book Digital Signal Processing and Spectral Analysis for Scientists by Silvia Maria Alessio, Springer International Publishing
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Author: Silvia Maria Alessio ISBN: 9783319254685
Publisher: Springer International Publishing Publication: December 9, 2015
Imprint: Springer Language: English
Author: Silvia Maria Alessio
ISBN: 9783319254685
Publisher: Springer International Publishing
Publication: December 9, 2015
Imprint: Springer
Language: English

This book covers the basics of processing and spectral analysis of monovariate discrete-time signals. The approach is practical, the aim being to acquaint the reader with the indications for and drawbacks of the various methods and to highlight possible misuses. The book is rich in original ideas, visualized in new and illuminating ways, and is structured so that parts can be skipped without loss of continuity. Many examples are included, based on synthetic data and real measurements from the fields of physics, biology, medicine, macroeconomics etc., and a complete set of MATLAB exercises requiring no previous experience of programming is provided. Prior advanced mathematical skills are not needed in order to understand the contents: a good command of basic mathematical analysis is sufficient. Where more advanced mathematical tools are necessary, they are included in an Appendix and presented in an easy-to-follow way. With this book, digital signal processing leaves the domain of engineering to address the needs of scientists and scholars in traditionally less quantitative disciplines, now facing increasing amounts of data.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

This book covers the basics of processing and spectral analysis of monovariate discrete-time signals. The approach is practical, the aim being to acquaint the reader with the indications for and drawbacks of the various methods and to highlight possible misuses. The book is rich in original ideas, visualized in new and illuminating ways, and is structured so that parts can be skipped without loss of continuity. Many examples are included, based on synthetic data and real measurements from the fields of physics, biology, medicine, macroeconomics etc., and a complete set of MATLAB exercises requiring no previous experience of programming is provided. Prior advanced mathematical skills are not needed in order to understand the contents: a good command of basic mathematical analysis is sufficient. Where more advanced mathematical tools are necessary, they are included in an Appendix and presented in an easy-to-follow way. With this book, digital signal processing leaves the domain of engineering to address the needs of scientists and scholars in traditionally less quantitative disciplines, now facing increasing amounts of data.

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