SMARTPHONE-BASED REAL-TIME DIG

Third Auflage
ISBN: 978-1-68173-945-8
Verlag: MORGAN & CLAYPOOL

Buch, Englisch, 174 Seiten, Paperback, Format (B × H): 191 mm x 235 mm

Reihe: Synthesis Lectures on Signal Processing

Real-time or applied digital signal processing courses are offered as follow-ups to conventional or theory-oriented digital signal processing courses in many engineering programs for the purpose of teaching students the technical know-how for putting signal processing algorithms or theory into practical use. These courses normally involve access to a teaching laboratory that is equipped with hardware boards, in particular DSP boards, together with their supporting software. A number of textbooks have been written discussing how to achieve real-time implementation on these hardware boards. This book discusses how to use smartphones as hardware boards for real-time implementation of signal processing algorithms, thus providing an alternative to the hardware boards that are used in signal processing laboratory courses. The fact that mobile devices, in particular smartphones, have become powerful processing platforms led to the development of this book to enable students to use their own smartphones to run signal processing algorithms in real-time considering that these days nearly all students possess smartphones. Changing the hardware platforms that are currently used in applied or real-time signal processing courses to smartphones creates a truly flexible laboratory experience or environment for students. In addition, it relieves the cost burden associated with using dedicated signal processing boards noting that the software development tools for smartphones are free of charge and are well-maintained by smartphone manufacturers. This book is written in such a way that it can be used as a textbook for real-time or applied digital signal processing courses offered at many universities. Ten lab experiments that are commonly encountered in such courses are covered in the book. It is written primarily for those who are already familiar with signal processing concepts and are interested in their real-time and practical aspects. Similar to existing real-time courses, knowledge of C programming is assumed. This book can also be used as a self-study guide for those who wish to become familiar with signal processing app development on either Android or iOS smartphones/tablets.

Autoren/Hrsg.

Fachgebiete

• Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Handheld Programmierung
• Technische Wissenschaften Sonstige Technologien | Angewandte Technik Signalverarbeitung, Bildverarbeitung, Scanning

Inhaltsverzeichnis

- Preface
- Introduction
- Android Software Development Tools
- iOS Software Development Tools
- Analog-to-Digital Signal Conversion
- Fixed-Point vs. Floating-Point
- Real-Time Filtering
- Adaptive Filtering
- Domain Transforms
- Code Optimization
- Implementation via MATLAB Coder
- Authors' Biographies

Über Autor(innen)

Nasser Kehtarnavaz is an Erik Jonsson Distinguished Professor in the Department of Electrical and Computer Engineering at the University of Texas at Dallas. His research areas include signal and image processing, real-time implementation on embedded processors, and deep learning. He has authored or co-authored more than 400 publications and 9 other books pertaining to signal and image processing, and regularly teaches an applied digital signal processing course, for which this book was developed. Dr. Kehtarnavaz is a Fellow of IEEE, a Fellow of SPIE, and a licensed Professional Engineer.

Abhishek Sehgal is a Senior Research Engineer at Samsung Research America. He received his B.E. degree in Instrumentation Technology from Visvesvaraya Technological University in India in 2012, and his M.S. and Ph.D. degrees in Electrical Engineering from the University of Texas at Dallas in 2015 and 2019, respectively. His research interests include signal and image processing, and real-time implementation of signal and image processing algorithms.

Shane Parris is a Software Engineer at Ford Motor Company. He received his B.S. degree in Electrical Engineering from the University of Texas at Dallas in 2013. His research interests include signal and image processing, and real-time implementation of signal and image processing algorithms.

Arian Azarang is a Ph.D. candidate in the Department of Electrical and Computer Engineering at the University of Texas at Dallas. His research interests include signal and image processing, deep learning, remote sensing, and chaos theory. He has authored or co-authored 14 publications in these areas.