Signal Processing for Intelligent Sensor Systems with MATLAB®

Description

Signal Processing for Intelligent Sensors with MATLAB ® , Second Edition once again presents the key topics and salient information required for sensor design and application. Organized to make it accessible to engineers in school as well as those practicing in the field, this reference explores a broad array of subjects and is divided into sections: Fundamentals of Digital Signal... Read more

Signal Processing for Intelligent Sensors with MATLAB^®, Second Edition once again presents the key topics and salient information required for sensor design and application. Organized to make it accessible to engineers in school as well as those practicing in the field, this reference explores a broad array of subjects and is divided into sections: Fundamentals of Digital Signal Processing, Frequency Domain Processing, Adaptive System Identification and Filtering, Wavenumber Sensor Systems, and Signal Processing Applications.

Taking an informal, application-based approach and using a tone that is more engineer-to-engineer than professor-to-student, this revamped second edition enhances many of the features that made the original so popular. This includes retention of key algorithms and development methodologies and applications, which are creatively grouped in a way that differs from most comparable texts, to optimize their use.

New for the Second Edition:

Inclusion of more solved problems
Web access to a large collection of MATLAB^® scripts used to support data graphs presented throughout the book
Additional coverage of more audio engineering, transducers, and sensor networking technology
A new chapter on Digital Audio processing reflects a growing interest in digital surround sound (5.1 audio) techniques for entertainment, home theaters, and virtual reality systems
New sections on sensor networking, use of meta-data architectures using XML, and agent-based automated data mining and control

Serving dual roles as both a learning resource and a field reference on sensor system networks, this book progressively reveals digestible nuggets of critical information to help readers quickly master presented algorithms and adapt them to meet their requirements. It illustrates the current trend toward agile development of web services for wide area sensor networking and intelligent processing in the sensor system networks that are employed in homeland security, business, and environmental and demographic information systems.

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Fourier Transform
Mathematical Basis for the Fourier Transform
Spectral Resolution
Fast Fourier Transform
Data Windowing
Circular Convolution Issues
Uneven-Sampled Fourier Transforms
Wavelet and Chirplet Transforms

Spectral Density
Spectral Density Derivation
Statistical Metrics of Spectral Bins
Transfer Functions and Spectral Coherence
Intensity Field Theory
Intensity Display and Measurement Techniques

Wavenumber Transforms
Spatial Transforms
Spatial Filtering and Beamforming
Image Enhancement Techniques
JPEG and MPEG Compression Techniques
Computer-Aided Tomography
Magnetic Resonance Imaging

Part III: Adaptive System Identification and Filtering

Linear Least-Squared Error Modeling
Block Least Squares
Projection-Based Least Squares
General Basis System Identification

Recursive Least-Squares Techniques
RLS Algorithm and Matrix Inversion Lemma
LMS Convergence Properties
Lattice and Schur Techniques
Adaptive Least-Squares Lattice Algorithm

Recursive Adaptive Filtering
Adaptive Kalman Filtering
IIR Forms for LMS and Lattice Filters
Frequency Domain Adaptive Filters

Part IV: Wavenumber Sensor Systems

Signal Detection Techniques
Rician PDF
RMS, CFAR Detection, and ROC Curves
Statistical Modeling of Multipath

Wavenumber and Bearing Estimation
Cramer–Rao Lower Bound
Bearing Estimation and Beam Steering
Field Reconstruction Techniques
Wave Propagation Modeling

Adaptive Beamforming and Localization
Array "Null-Forming"
Eigenvector Methods of MUSIC and MVDR
Coherent Multipath Resolution Techniques
FMCW and Synthetic Aperture Processing

Part V: Signal Processing Applications

Noise Reduction Techniques
Electronic Noise
Noise Cancellation Techniques
Active Noise Attenuation

Sensors and Transducers
Simple Transducer Signals
Acoustic and Vibration Sensors
Chemical and Biological Sensors
Nuclear Radiation Sensors

Intelligent Sensor Systems
Automatic Target Recognition Algorithms
Signal and Image Features
Dynamic Feature Tracking and Prediction
Intelligent Sensor Agents

Author(s)

Biography

David C. Swanson

Signal Processing for Intelligent Sensor Systems with MATLAB®

Description

Table of Contents

Author(s)

Biography

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