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Fundamentals of Signal Processing for Sound and Vibration Engineers

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ISBN-10: 0470511885

ISBN-13: 9780470511886

Edition: 2008

Authors: Kihong Shin, Joseph Hammond

List price: $139.95
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Description:

An excellent reference for the signal processing field this book includes material on both random signals and deterministic signals in one volume. It combines signal processing theory with worked MATLAB problems and solutions chapter by chapter it integrates topics in continuous, discrete, deterministic, and random signals, for a better overall understanding of the topic. Fundamentals of Signal Processing also provides a structured guide to signal processing for sound and vibration engineers, as well as acting as a reference for those in mechanical, automotive, aerospace, and civil engineering.
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Book details

List price: $139.95
Copyright year: 2008
Publisher: John Wiley & Sons, Incorporated
Publication date: 4/21/2008
Binding: Hardcover
Pages: 416
Size: 6.95" wide x 9.90" long x 1.10" tall
Weight: 1.826
Language: English

Joseph (Joe) Hammond graduated in Aeronautical Engineering in 1966 at the University of Southampton. He completed his PhD in the Institute of Sound and Vibration Research (ISVR) in 1972 whilst a lecturer in the Mathematics Department at Portsmouth Polytechnic. He returned to Southampton in 1978 as a lecturer in the ISVR, and was later Senior lecturer, Professor, Deputy Director and then Director of the ISVR from 1992-2001. In 2001 he became Dean of the Faculty of Engineering and Applied Science, and in 2003 Dean of the Faculty of Engineering, Science and Mathematics. he retired in July 2007 and is an Emeritus Professor at Southampton. Kihong Shin graduated in Precision Mechanical…    

Preface
About the Authors
Introduction to Signal Processing
Descriptions of Physical Data (Signals)
Classification of Data
Deterministic Signals
Classification of Deterministic Data
Periodic Signals
Almost Periodic Signals
Transient Signals
Brief Summary and Concluding Remarks
MATLAB Examples
Fourier Series
Periodic Signals and Fourier Series
The Delta Function
Fourier Series and the Delta Function
The Complex Form of the Fourier Series
Spectra
Some Computational Considerations
Brief Summary
MATLAB Examples
Fourier Integrals (Fourier Transform) and Continuous-Time Linear Systems
The Fourier Integral
Energy Spectra
Some Examples of Fourier Transforms
Properties of Fourier Transforms
The Importance of Phase
Echoes
Continuous-Time Linear Time-Invariant Systems and Convolution
Group Delay (Dispersion)
Minimum and Non-Minimum Phase Systems
The Hilbert Transform
The Effect of Data Truncation (Windowing)
Brief Summary
MATLAB Examples
Time Sampling and Aliasing
The Fourier Transform of an Ideal Sampled Signal
Aliasing and Anti-Aliasing Filters
Analogue-to-Digital Conversion and Dynamic Range
Some Other Considerations in Signal Acquisition
Shannon's Sampling Theorem (Signal Reconstruction)
Brief Summary
MATLAB Examples
The Discrete Fourier Transform
Sequences and Linear Filters
Frequency Domain Representation of Discrete Systems and Signals
The Discrete Fourier Transform
Properties of the DFT
Convolution of Periodic Sequences
The Fast Fourier Transform
Brief Summary
MATLAB Examples
Introduction to Random Processes
Random Processes
Basic Probability Theory
Random Variables and Probability Distributions
Expectations of Functions of a Random Variable
Brief Summary
MATLAB Examples
Stochastic Processes; Correlation Functions and Spectra
Probability Distribution Associated with a Stochastic Process
Moments of a Stochastic Process
Stationarity
The Second Moments of a Stochastic Process; Covariance (Correlation) Functions
Ergodicity and Time Averages
Examples
Spectra
Brief Summary
MATLAB Examples
Linear System Response to Random Inputs: System Identification
Single-Input Single-Output Systems
The Ordinary Coherence Function
System Identification
Brief Summary
MATLAB Examples
Estimation Methods and Statistical Considerations
Estimator Errors and Accuracy
Mean Value and Mean Square Value
Correlation and Covariance Functions
Power Spectral Density Function
Cross-spectral Density Function
Coherence Function
Frequency Response Function
Brief Summary
MATLAB Examples
Multiple-Input/Response Systems
Description of Multiple-Input, Multiple-Output (MIMO) Systems
Residual Random Variables, Partial and Multiple Coherence Functions
Principal Component Analysis
Proof of [characters not reproducible]
Proof of [characters not reproducible]
Wave Number Spectra and an Application
Some Comments on the Ordinary Coherence Function [gamma superscript 2 subscript xy](f)
Least Squares Optimization: Complex-Valued Problem
Proof of H[subscript W](f) to H[subscript 1](f) as [kappa](f) to [infinity]
Justification of the Joint Gaussianity of X(f)
Some Comments on Digital Filtering
References
Index