Swanson D.C. Signal Processing for Intelligent Sensor Systems with MatLAB

CRC Press, 2012, -664 p.The second edition of Signal Processing for Intelligent Sensor Systems enhances many of the unique features of the first edition with more answered problems, web access to a large collection of MatLAB scripts used throughout the book, and the addition of more audio engineering, transducers, and sensor networking technology. All of the key algorithms and development methodologies have been kept from the first edition, and hopefully all of the typographical errors have been fixed. The addition of a 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. Also, new sections are added in the areas of sensor networking, use of meta-data architectures using XML, and agent-based automated data mining and control. This later information really ties large-scale networks of intelligent sensors together as a network of thin file servers. Intelligent algorithms, either resident in the sensor/file-server nodes, or run remotely across the network as intelligent agents, can then provide an automated situational awareness. The many algorithms presented in Signal Processing for Intelligent Sensor Systems can then be applied locally or network-based to realize elegant solutions to very complex detection problems.It was nearly 20 years ago that I was asked to consider writing a textbook on signal processing for sensors. At the time I typically had over a dozen textbooks on my desk, each with just a few small sections bookmarked for frequent reference. The genesis of this book was to bring together all these key subjects into one text, summarize the salient information needed for design and application, and organize the broad array of sensor signal processing subjects in a way to make it accessible to engineers in school as well as those practicing in the field. The discussion herein is somewhat informal and applied and in a tone of engineer-to-engineer, rather than professor-to-student. There are many subtle nuggets of critical information revealed that should help most readers quickly master the algorithms and adapt them to meet their requirements. This text is both a learning resource and a field reference. In support of this, every data graph in the text has a MatLAB m-script in support of it and these m-scripts are kept simple, commented, and made available to readers for download from the CRC Press website for the book. Taylor & Francis Group (CRC Press) acquired the rights to the first edition and have been relentless in encouraging me to update it in this second edition. There were also a surprising number of readers who found me online and encouraged me to make an updated second edition. Given the high cost of textbooks and engineering education, we are excited to cut the price significantly, make the book available electronically online, as well as for rent electronically which should be extremely helpful to students on a tight budget. Each chapter has a modest list of solved problems (answer book available from the publisher) and references for more information.Part I Fundamentals of Digital Signal Processing
Sampled Data Systems
z-Transform
Digital Filtering
Digital Audio Processing
Linear Filter Applications
Part II Frequency Domain Processing
Fourier Transform
Spectral Density
Wavenumber Transforms
Part III Adaptive System Identification and Filtering
Linear Least-Squared Error Modeling
Recursive Least-Squares Techniques
Recursive Adaptive Filtering
Part IV Wavenumber Sensor Systems
Signal Detection Techniques
Wavenumber and Bearing Estimation
Adaptive Beamforming and Localization
Part V Signal Processing Applications
Noise Reduction Techniques
Sensors and Transducers
Intelligent Sensor Systems