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.
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[ELSEVIER Academic Press LOGO]
Biomedical Engineering, Electrical Engineering, Biomathematics
Introduction to Applied Statistical Signal Analysis
Guide to Biomedical and Electrical Engineering Applications, 3rd Ed
Richard Shiavi
Vanderbilt University, Nashville, Tennessee, U.S.A.
KEY FEATURES
· Notebooks provide an interactive mode of learning that can be utilized by professors or independent learners
· Online materials include detailed quantitative examples presented with Mat Lab implementation
· Over one hundred worked problems, real world applications, graphs, and notebook applications
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.
Contents:
Introduction to Terminology; Empirical Modeling and Approximation; Fourier Analysis; Probability Concepts and Signal Characteristics; Random Processes and Signal Correlation; Random Signals, Linear Systems, and Power Spectra; Spectral Analysis for Random Signals; Random Signal Modeling and Modern Spectral Estimation; Theory and Application of Cross Correlation and Coherence
Related titles:
Enderle; Introduction to Biomedical Engineering, 2 ed.; 0122386620; April 2005|[ELSEVIER Academic Press LOGO]
Biomedical Engineering, Electrical Engineering, Biomathematics
Introduction to Applied Statistical Signal Analysis
Guide to Biomedical and Electrical Engineering Applications, 3rd Ed
Richard Shiavi
Vanderbilt University, Nashville, Tennessee, U.S.A.
KEY FEATURES
· Notebooks provide an interactive mode of learning that can be utilized by professors or independent learners
· Online materials include detailed quantitative examples presented with Mat Lab implementation
· Over one hundred worked problems, real world applications, graphs, and notebook applications
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.
Contents:
Introduction to Terminology; Empirical Modeling and Approximation; Fourier Analysis; Probability Concepts and Signal Characteristics; Random Processes and Signal Correlation; Random Signals, Linear Systems, and Power Spectra; Spectral Analysis for Random Signals; Random Signal Modeling and Modern Spectral Estimation; Theory and Application of Cross Correlation and Coherence
Related titles:
Enderle; Introduction to Biomedical Engineering, 2 ed.; 0122386620; April 2005
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.
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