Introduction to Applied Statistical Signal Analysis Guide to Biomedical and Electrical Engineering Applications

The third edition of "Introduction to Applied Statistical Signal Analysis" begins with a discussion of techniques for modeling and represents discrete data measurements, interpolation, and a definition of time series. Building from basic principles to illustrate complex application, this book provides a practical introduction to signal analysis techniques that are commonly used in a broad range of engineering areas including speech, biomedical signals, communications, and pattern recognition.
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.
Balanced perspective of the concepts, mathematical bases, and requirements for estimation
Online materials include detailed quantitative examples presented with Mat Lab implementation
Over one hundred worked problems, real world applications, graphs, and notebook applications to further the understanding of concepts

Introduction to Applied Statistical Signal Analysis 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.

Introduction to Applied Statistical Signal Analysis intertwines theory and implementation with practical examples and exercises. Topics presented in detail include: mathematical bases, requirements for estimation and detailed quantitative examples for implementing techniques for classical signal analysis. This book will help readers understand real-world applications of signal analysis as they relate to biomedical engineering.


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.

· Accompanied by MATLAB notebooks that provide an interactive mode of learning which can be utilized by professors or independent learners, available from the Companion website.
· 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. Copies of these are available for download from the Companion website.
· Please visit http://books.elsevier.com/companions/9780120885817 to access accompanying material.

Richard Shiavi is Professor of Biomedical Engineering and Professor of Electrical Engineering, actively engaged in teaching and research at Vanderbilt University and the Veterans Administration Medical Center. His main professional interests are in signal processing and main research interests are in bioelectric signal processing and signal measurement. Dr. Shiavi has been an active member of Institute of Electrical and Electronic Engineers (IEEE) and the IEEE Engineering in Medicine and Biology Society (EMBS) and is presently an Associate Editor for the Transactions on Biomedical Engineering. He is also an active member and past President of the International Society of Electrophysiology and Kinesiology.