The method of sparsity has been attracting a lot of attention in the fields related not only to signal processing, machine learning, and statistics, but also systems and control. The method is known as compressed sensing, compressive sampling, sparse representation, or sparse modeling. More recently, the sparsity method has been applied to systems and control to design resource-aware control systems. This book gives a comprehensive guide to sparsity methods for systems and control, from standard sparsity methods in finite-dimensional vector spaces (Part I) to optimal control methods in infinite-dimensional function spaces (Part II).

The primary objective of this book is to show how to use sparsity methods for several engineering problems. For this, the author provides MATLAB programs by which the reader can try sparsity methods for themselves. Readers will obtain a deep understanding of sparsity methods by running these MATLAB programs.

Sparsity Methods for Systems and Control is suitable for graduate level university courses, though it should also be comprehendible to undergraduate students who have a basic knowledge of linear algebra and elementary calculus. Also, especially part II of the book should appeal to professional researchers and engineers who are interested in applying sparsity methods to systems and control.

About the Author

Dr. Masaaki Nagahara received the bachelor's degree in engineering from Kobe University in 1998, and the master's degree and the Doctoral degree in informatics from Kyoto University in 2000 and 2003, respectively.

He is currently a Full Professor with the Institute of Environmental Science and Technology, The University of Kitakyushu. He has been a Visiting Professor with Indian Institute of Technology Bombay since 2017. His research interests include control theory, machine learning, and sparse modeling.

He received Transition to Practice Award in 2012 and George S. Axelby Outstanding Paper Award in 2018 from IEEE Control Systems Society. He also received Young Authors Award in 1999, Best Paper Award in 2012, and Best Book Authors Award in 2016, from SICE, and Best Tutorial Paper Award in 2014 from IEICE Communications Society.

He is a senior member of IEEE.

"About this title" may belong to another edition of this title.

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