Signal Analysis
Time, Frequency, Scale, and Structure
Published on 20. January 2004
Book
Hardback
966 pages
978-0-471-23441-8 (ISBN)
Description
Offers a well-rounded, mathematical approach to problems in signal interpretation using the latest time, frequency, and mixed-domain methods
* Equally useful as a reference, an up-to-date review, a learning tool, and a resource for signal analysis techniques
* Provides a gradual introduction to the mathematics so that the less mathematically adept reader will not be overwhelmed with instant hard analysis
* Covers Hilbert spaces, complex analysis, distributions, random signals, analog Fourier transforms, and more
More details
Product info
gebunden
Edition
1. Auflage
Language
English
Place of publication
United States
Publishing group
John Wiley & Sons Inc
Target group
Professional and scholarly
Product notice
sewn/stitched
Cloth over boards
Illustrations
Drawings: 200 B&W, 0 Color
Dimensions
Height: 240 mm
Width: 161 mm
Thickness: 55 mm
Weight
1587 gr
ISBN-13
978-0-471-23441-8 (9780471234418)
Schweitzer Classification
Other editions
Additional editions
E-Book
05/2004
Wiley-IEEE Press
€149.99
Available for download
Persons
RONALD L. ALLEN received his BA in mathematics from the University of California, Berkeley in 1973, his MA in mathematics from the University of California, Los Angeles in 1975, and his MS and PhD in Computer Science from the University of Texas at Arlington in 1990 and 1993, respectively.
DUNCAN W. MILLS received his BA in Physics from Wesleyan University, his MS in Electrical Engineering from George Washington University, and his PhD in Electrical Engineering from University of Texas at Dallas in 1992.
Content
Preface.
Acknowledgments.
1 Signals: Analog, Discrete, and Digital.
1.1 Introduction to Signals.
1.2 Analog Signals.
1.3 Discrete Signals.
1.4 Sampling and Interpolation.
1.5 Periodic Signals.
1.6 Special Signal Classes.
1.7 Signals and Complex Numbers.
1.8 Random Signals and Noise.
1.9 Summary.
References.
Problems.
2 Discrete Systems and Signal Spaces.
2.1 Operations on Signals.
2.2 Linear Systems.
2.3 Translation Invariant Systems.
2.4 Convolutional Systems.
2.5 The l¯p Signal Spaces.
2.6 Inner Product Spaces.
2.7 Hilbert Spaces.
2.8 Summary.
References.
Problems.
3 Analog Systems and Signal Spaces.
3.1 Analog Systems.
3.2 Convolution and Analog LTI Systems.
3.3 Analog Signal Spaces.
3.4 Modern Integration Theory.
3.5 Distributions.
3.6 Summary.
References.
Problems.
4 Time-Domain Signal Analysis.
4.1 Segmentation.
4.2 Thresholding.
4.3 Texture.
4.4 Filtering and Enhancement.
4.5 Edge Detection.
4.6 Pattern Detection.
4.7 Scale Space.
4.8 Summary.
References.
Problems.
5 Fourier Transforms of Analog Signals.
5.1 Fourier Series.
5.2 Fourier Transform.
5.3 Extension to L2(R).
5.4 Summary.
References.
Problems.
6 Generalized Fourier Transforms of Analog Signals.
6.1 Distribution Theory and Fourier Transforms.
6.2 Generalized Functions and Fourier Series Coefficients.
6.3 Linear Systems in the Frequency Domain.
6.4 Introduction to Filters.
6.5 Modulation.
6.6 Summary.
References.
Problems.
7 Discrete Fourier Transforms.
7.1 Discrete Fourier Transform.
7.2 Discrete-Time Fourier Transform.
7.3 The Sampling Theorem.
7.4 Summary.
References.
Problems.
8 The z-Transform.
8.1 Conceptual Foundations.
8.2 Inversion Methods.
8.3 Related Transforms.
8.4 Summary.
References.
Problems.
9 Frequency-Domain Signal Analysis.
9.1 Narrowband Signal Analysis.
9.2 Frequency and Phase Estimation.
9.3 Discrete filter design and implementation.
9.4 Wideband Signal Analysis.
9.5 Analog Filters.
9.6 Specialized Frequency-Domain Techniques.
9.7 Summary.
References.
Problems.
10 Time-Frequency Signal Transforms.
10.1 Gabor Transforms.
10.2 Short-Time Fourier Transforms.
10.3 Discretization.
10.4 Quadratic Time-Frequency Transforms.
10.5 The Balian-Low Theorem.
10.6 Summary.
References.
Problems.
11 Time-Scale Signal Transforms.
11.1 Signal Scale.
11.2 Continuous Wavelet Transforms.
11.3 Frames.
11.4 Multiresolution Analysis and Orthogonal Wavelets.
11.5 Summary.
References.
Problems.
12 Mixed-Domain Signal Analysis.
12.1 Wavelet Methods for Signal Structure.
12.2 Mixed-Domain Signal Processing.
12.3 Biophysical Applications.
12.4 Discovering Signal Structure.
12.5 Pattern Recognition Networks.
12.6 Signal Modeling and Matching.
12.7 Afterword.
References.
Problems.
Index.