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Author Shiavi, Richard.

Title Introduction to applied statistical signal analysis : guide to biomedical and electrical engineering applications / Richard Shiavi.

Imprint Amsterdam ; Boston : Elsevier Academic Press, ©2007.

Copies

Location Call No. OPAC Message Status
 Axe Books 24x7 Engineering E-Book  Electronic Book    ---  Available
Edition 3rd ed.
Description 1 online resource (xxii, 402 pages) : illustrations
text txt rdacontent
computer c rdamedia
online resource cr rdacarrier
Bibliography Includes bibliographical references and index.
Contents Cover -- Copyright Page -- Table of Contents -- Preface -- Dedication -- Acknowledgments -- List of symbols -- Chapter 1 Introduction and terminology -- 1.1 Introduction -- 1.2 Signal terminology -- 1.2.1 Domain Types -- 1.2.2 Amplitude Types -- 1.2.3 Basic Signal Forms -- 1.2.4 The Transformed Domain-The Frequency Domain -- 1.2.5 General Amplitude Properties -- 1.3 Analog to digital conversion -- 1.4 Measures of signal properties -- 1.4.1 Time Domain -- 1.4.2 Frequency Domain -- References -- Chapter 2 Empirical modeling and approximation -- 2.1 Introduction -- 2.2 Model development -- 2.3 Generalized least squares -- 2.4 Generalities -- 2.5 Models from linearization -- 2.6 Orthogonal polynomials -- 2.7 Interpolation and extrapolation -- 2.7.1 Lagrange Polynomials -- 2.7.2 Spline Interpolation -- 2.8 Overview -- References -- Exercises -- Chapter 3 Fourier analysis -- 3.1 Introduction -- 3.2 Review of fourier series -- 3.2.1 Definition -- 3.2.2 Convergence -- 3.3 Overview of fourier transform relationships -- 3.3.1 Continuous versus Discrete Time -- 3.3.2 Discrete Time and Frequency -- 3.4 Discrete fourier transform -- 3.4.1 Definition Continued -- 3.4.2 Partial Summary of DFT Properties and Theorems -- 3.5 Fourier analysis -- 3.5.1 Frequency Range and Scaling -- 3.5.2 The Effect of Discretizing Frequency -- 3.5.3 The Effect of Truncation -- 3.5.4 Windowing -- 3.5.5 Resolution -- 3.5.6 Detrending -- 3.6 Procedural summary -- 3.7 Selected applications -- References -- Exercises -- Appendices -- Appendix 3.1 DFT of ionosphere data -- Appendix 3.2 Review of properties of orthogonal functions -- Appendix 3.3 The fourier transform -- Appendix 3.4 Data and spectral windows -- Chapter 4 Probability concepts and signal characteristics -- 4.1 Introduction -- 4.2 Introduction to random variables -- 4.2.1 Probability Descriptors -- 4.2.2 Moments of Random Variables -- 4.2.3 Gaussian Random Variable -- 4.3 Joint probability -- 4.3.1 Bivariate Distributions -- 4.3.2 Moments of Bivariate Distributions -- 4.4 Concept of sampling and estimation -- 4.4.1 Sample Moments -- 4.4.2 Significance of the Estimate -- 4.5 Density function estimation -- 4.5.1 General Principle for χ2 Approach -- 4.5.2 Detailed Procedure for χ2 Approach -- 4.5.3 Quantile-Quantile Approach -- 4.6 Correlation and regression -- 4.6.1 Estimate of Correlation -- 4.6.2 Simple Regression Model -- 4.7 General properties of estimators -- 4.7.1 Convergence -- 4.7.2 Recursion -- 4.7.3 Maximum Likelihood Estimation -- 4.8 Random numbers and signal characteristics -- 4.8.1 Random Number Generation -- 4.8.2 Change of Mean and Variance -- 4.8.3 Density Shaping -- References -- Exercises -- Appendices -- Appendix 4.1 Plots and formulas for five probability density functions -- Chapter 5 Introduction to random processes and signal properties -- 5.1 Introduction -- 5&#4.
Note Print version record.
Summary 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.
Subject Signal processing -- Statistical methods.
Traitement du signal -- Méthodes statistiques.
COMPUTERS -- Information Theory.
TECHNOLOGY & ENGINEERING -- Signals & Signal Processing.
Signal processing -- Statistical methods. (OCoLC)fst01118304
Genre/Form Electronic books.
Other Form: Print version: Shiavi, Richard. Introduction to applied statistical signal analysis. 3rd ed. Amsterdam ; Boston : Elsevier Academic Press, ©2007 0120885816 9780120885817 (OCoLC)70059536
ISBN 9780080467689 (electronic bk.)
0080467687 (electronic bk.)
0120885816 (Cloth)
Standard No. DEBBG BV043113030
DEBSZ 422224111
GBVCP 802260500

 
    
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