This book is the outgrowth of our teaching advanced undergraduate and graduate courses over the past 20 years. These courses have been taught to different audiences, including students in electrical and electronics engineering, computer engineering, computer science, and informatics, as well as to an interdisciplinary audience of a graduate course on automation. This experience led us to make the book as self-contained as possible and to address students with different backgrounds. As prerequisitive knowledge, the reader requires only basic calculus, elementary linear algebra, and some probability theory basics. A number of mathematical tools, such as probability and statistics as well as constrained optimization, needed by various chapters, ...

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