Smartphone-Based Real-Time Digital Signal Processing

Smartphone-Based Real-Time Digital Signal Processing

Nasser Kehtarnavaz, Shane Parris, Abishek Sehgal
ISBN: 9781627058162 | PDF ISBN: 9781627058179
Copyright © 2015 | 157 Pages | Publication Date: August, 2015

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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 smartphones can be used as hardware boards for real-time implementation of signal processing algorithms as an alternative to the hardware boards that are currently being used in signal processing teaching laboratories. The fact that mobile devices, in particular smartphones, have now become powerful processing platforms has led to the development of this book, thus 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 a dedicated signal processing board noting that the software development tools for smartphones are free of charge and are well-developed. This book is written in such a way that it can be used as a textbook for applied or real time 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. All the lab codes can be obtained as a software package from THIS SITE.

Table of Contents

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

About the Author(s)

Nasser Kehtarnavaz, University of Texas, Dallas
Nasser Kehtarnavaz is Professor of Electrical Engineering at University of Texas at Dallas. His research areas include digital signal and image processing, real-time processing on embedded processors, pattern recognition, and biomedical image analysis. He has published more than 300 articles in these areas and 8 other books pertaining to signal and image processing. He regularly teaches applied digital signal processing courses, for which this book is intended. Dr. Kehtarnavaz is a Fellow of IEEE, a Fellow of SPIE, and a licensed Professional Engineer. Among his many professional activities, he is serving as Editor-in-Chief of Journal of Real-Time Image Processing.

Shane Parris, University of Texas, Dallas
Shane Parris received his BS degree in Electrical Engineering from University of Texas at Dallas in 2013. He is currently pursuing his MS degree in Electrical Engineering at the University of Texas at Dallas. His research interests include signal and image processing, and real-time implementation of signal and image processing algorithms.

Abishek Sehgal, University of Texas, Dallas
Abhishek Sehgal received his BE degree in Instrumentation Technology from Visvesvaraya Technological University in India in 2012. He is currently pursuing his MS degree in Electrical Engineering at the University of Texas at Dallas. His research interests include signal and image processing, and real-time implementation of signal and image processing algorithms.

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