Beschreibung
A typical undergraduate electrical engineering curriculum incorporates a signals and systems course. The widely used approach for the laboratory component of such courses involves the utilization of MATLAB to implement signals and systems concepts. This book presents a newly developed laboratory paradigm where MATLAB codes are made to run on smartphones which are possessed by nearly all students. As a result, this laboratory paradigm provides an anywhere-anytime hardware platform or processing board for students to learn implementation aspects of signals and systems concepts. The book covers the laboratory experiments that are normally covered in signals and systems courses and discusses how to run MATLAB codes for these experiments as apps on both Android and iOS smartphones, thus enabling a truly mobile laboratory paradigm. A zipped file of the codes discussed in the book can be acquired via the website http://sites.fastspring.com/bookcodes/product/SignalsSystemsBookcodesThirdEdition
Autorenportrait
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 processing on embedded processors, deep learning, and machine learning. He has authored or co-authored more than 400 publications and 9 other books pertaining to signal and image processing, and regularly teaches the signals and systems laboratory course, for which this book is written. Dr. Kehtarnavaz is a Fellow of IEEE, a Fellow of SPIE, and a licensed Professional Engineer.Fatemeh Saki received her Ph.D. in Electrical Engineering from the University of Texas at Dallas in 2017. She is currently a Senior R&D Engineer at Qualcomm. Her research interests include signal and image processing, pattern recognition, and machine learning. Dr. Saki has authored or co-authored 20 publications in these areas.Adrian Duran received his M.S. in Electrical Engineering from the University of Texas at Dallas in 2018. He is currently a Signal Processing Analyst at Innovative Signal Analysis, Inc. His research interests are signal and image processing, pattern recognition, and machine learning.Arian Azarangis 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 12 publications in these areas.
