Signal Processing for Intelligent Sensor Systems with MATLAB

Signal Processing for Intelligent Sensor Systems with MATLAB®

Title: Signal Processing for Intelligent Sensor Systems with MATLAB®

Author: David C. Swanson

Publisher: CRC Press; 2 edition

Hardcover: 683 pages

Pubdate: 26 July 2011

ISBN: 1420043048

Book Description

Signal Processing for Intelligent Sensors, 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.

Table of Contents

Part I: Fundamentals of Digital Signal Processing

Sampled Data Systems

A/D Conversion

Sampling Theory

Complex Bandpass Sampling

Delta–Sigma Analog Conversion

z-Transform

Comparison of Laplace and z-Transforms

System Theory

Mapping of s-Plane Systems to the Digital Domain

Digital Filtering

FIR Digital Filter Design

IIR Filter Design and Stability

Whitening Filters, Invertibility, and Minimum Phase

Filter Basis Polynomials

Digital Audio Processing

Basic Room Acoustics

Artificial Reverberation and Echo Generators

Flanging and Chorus Effects

Bass, Treble, and Parametric Filters

Amplifier and Compression/Expansion Processors

Digital-to-Analog Reconstruction Filters

Audio File Compression Techniques

Linear Filter Applications

State Variable Theory

Fixed-Gain Tracking Filters

2D FIR Filters

Image Upsampling Reconstruction Filters

Part II: Frequency Domain Processing

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

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