
Introduction to Applied Statistical Signal Analysis
Guide to Biomedical and Electrical Engineering Applications
- 424 pages
- English
- PDF
- Available on iOS & Android
Introduction to Applied Statistical Signal Analysis
Guide to Biomedical and Electrical Engineering Applications
About this book
Introduction to Applied Statistical Signal Analysis, Third Edition, is designed for the experienced individual with a basic background in mathematics, science, and computer. With this predisposed knowledge, the reader will coast through the practical introduction and move on to signal analysis techniques, commonly used in a broad range of engineering areas such as biomedical engineering, communications, geophysics, and speech.Topics presented include mathematical bases, requirements for estimation, and detailed quantitative examples for implementing techniques for classical signal analysis. This book includes over one hundred worked problems and real world applications. Many of the examples and exercises use measured signals, most of which are from the biomedical domain.The presentation style is designed for the upper level undergraduate or graduate student who needs a theoretical introduction to the basic principles of statistical modeling and the knowledge to implement them practically.- Includes over one hundred worked problems and real world applications. Many of the examples and exercises in the book use measured signals, many from the biomedical domain.
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Information
Table of contents
- Front Cover
- Title Page
- Copyright Page
- Table of Contents
- Preface
- Dedication
- Acknowledgments
- List of symbols
- Chapter 1 Introduction and terminology
- Chapter 2 Empirical modeling and approximation
- Chapter 3 Fourier analysis
- Chapter 4 Probability concepts and signal characteristics
- Chapter 5 Introduction to random processes and signal properties
- Chapter 6 Random signals, linear systems, and power spectra
- Chapter 7 Spectral analysis for random signals: Nonparametric methods
- Chapter 8 Random signal modeling and parametric spectral estimation
- Chapter 9 Theory and application of cross correlation and coherence
- Chapter 10 Envelopes and kernel functions
- Appendices
- Index