Synopsis
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 as 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 enabling 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 mobile 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. This book 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 iPhone smartphones.
About the Author
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 digital signal and image processing, real-time processing on embedded processors, and deep learning. He has authored more than 380 publications and 9 other books pertaining to signal and image processing, and regularly teaches an applied DSP 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 received his B.E. in Instrumentation Technology from Visvesvaraya Technological University in India in 2012, his M.S. and Ph.D. in Electrical Engineering at 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 received his B.S. in Electrical Engineering from 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.
Prof. José M. F. Moura joined CMU in 1986 as a Professor of Electrical and Computer Engineering. Currently he holds also a courtesy appointment as Professor with the Department of BioMedical Engineering. Prior to joining CMU, he was on the faculty at Instituto Superior Técnico (IST), the Engineering School of the Technical University of Lisbon (Portugal). He has had visiting faculty appointments at MIT: in 1984-86 as Genrad Associate Professor of Electrical and Computer Engineering (visiting) and in 1999-2000 as visiting Professor of Electrical Engineering. He was also a visiting Research Scholar at the University of Southern California in the Summers of 1979-1981. He received his D.Sc. in Electrical Engineering and Computer Science from MIT where he also received his MSc. in Electrical Engineering and the Electrical Engineering degree. He holds a Licenciatura em Engenharia Electrotécnica from IST.
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