Book description
Building on the unique features that made the first edition a bestseller, this second edition includes additional solved problems and web access to the large collection of MATLAB scripts that are highlighted throughout the text. The book offers expanded coverage of audio engineering, transducers, and sensor networking technology. It also includes new chapters on digital audio processing, as well as acoustics and vibrations transducers. The text addresses the use of meta-data architectures using XML and agent-based automated data mining and control. The numerous algorithms presented can be applied locally or network-based to solve complex detection problems.
Table of contents
- Cover
- Half Title
- Title Page
- Copyright Page
- Dedication
- Table of Contents
- Preface
- Acknowledgments
- Author
-
Part I Fundamentals of Digital Signal Processing
- Chapter 1 Sampled Data Systems
- Chapter 2 z-Transform
- Chapter 3 Digital Filtering
-
Chapter 4 Digital Audio Processing
- 4.1 Basic Room Acoustics
- 4.2 Artificial Reverberation and Echo Generators
- 4.3 Flanging and Chorus Effects
- 4.4 Bass, Treble, and Parametric Filters
- 4.5 Amplifier and Compression/Expansion Processors
- 4.6 Digital-to-Analog Reconstruction Filters
- 4.7 Audio File Compression Techniques
- 4.8 MATLAB® Examples
- 4.9 Summary
- Problems
- References
- Chapter 5 Linear Filter Applications
-
Part II Frequency Domain Processing
- Chapter 6 Fourier Transform
-
Chapter 7 Spectral Density
- 7.1 Spectral Density Derivation
-
7.2 Statistical Metrics of Spectral Bins
- 7.2.1 Probability Distributions and PDFs
- 7.2.2 Statistics of the NPSD Bin
- 7.2.3 SNR Enhancement and the Zoom FFT
- 7.2.4 Conversion of Random Variables
- 7.2.5 Confidence Intervals for Averaged NPSD Bins
- 7.2.6 Synchronous Time Averaging
- 7.2.7 Higher-Order Moments
- 7.2.8 Characteristic Function
- 7.2.9 Cumulants and Polyspectra
- 7.3 Transfer Functions and Spectral Coherence
- 7.4 Intensity Field Theory
- 7.5 Intensity Display and Measurement Techniques
- 7.6 MATLAB® Examples
- 7.7 Summary
- Problems
- References
- Chapter 8 Wavenumber Transforms
-
Part III Adaptive System Identification and Filtering
- Chapter 9 Linear Least-Squared Error Modeling
- Chapter 10 Recursive Least-Squares Techniques
- Chapter 11 Recursive Adaptive Filtering
- Part IV Wavenumber Sensor Systems
-
Part V Signal Processing Applications
- Chapter 15 Noise Reduction Techniques
- Chapter 16 Sensors and Transducers
- Chapter 17 Intelligent Sensor Systems
- Index
Product information
- Title: Signal Processing for Intelligent Sensor Systems with MATLAB®, 2nd Edition
- Author(s):
- Release date: July 2011
- Publisher(s): CRC Press
- ISBN: 9781439896280
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