Mathematical foundations for signal processing, communications, and networking / edited by Erchin Serpedin, Thomas Chen, Dinesh Rajan.

"Mathematical Foundations for Signal Processing, Communications, and Networking describes mathematical concepts and results important in the design, analysis, and optimization of signal processing algorithms, modern communication systems, and networks. Helping readers master key techniques and comprehend the current research literature, the book offers a comprehensive overview of methods and applications from linear algebra, numerical analysis, statistics, probability, stochastic processes, and optimization.From basic transforms to Monte Carlo simulation to linear programming, the text covers a broad range of mathematical techniques essential to understanding the concepts and results in signal processing, telecommunications, and networking. Along with discussing mathematical theory, each self-contained chapter presents examples that illustrate the use of various mathematical concepts to solve different applications. Each chapter also includes a set of homework exercises and pointers to further readings for additional topics and applications.This text helps readers understand fundamental and advanced results as well as recent research trends in the interrelated fields of signal processing, telecommunications, and networking. It provides all the necessary mathematical background to prepare students for more advanced courses and train specialists working in these areas"--

"Preface The rationale behind this textbook is to provide all the necessary mathematical background to facilitate the training and education of students and specialists working in the interrelated elds of signal processing, telecommunications and networking. Our intention was to create a self-contained textbook that contains both the fundamental results in the areas of signal processing, telecommunications and networking as well as the more advanced results and recent research trends in these areas. In our collective academic experience, students often begin their graduate education with widely varying undergraduate backgrounds in terms of needed subjects such as probability theory, stochastic processes, statistics, linear algebra, calculus, optimization techniques, game theory and queuing theory. While some students are well prepared for advanced courses in signal processing, telecommunications and networking, others are not as well prepared and must make extra remedial e orts. However, obtaining the necessary mathematical background is often difficult because these topics are usually dispersed across a large number of courses, where the emphasis is frequently put on topics di erent than signal processing, telecommunications and networking. We hope that this textbook will serve as a reference for graduate level students to reach a common standard level of preparedness before undertaking more advanced specialized studies. We believe that this book will be also useful for researchers, engineers, and scientists working in related areas in electrical engineering, computer science, bioinformatics and system biology"--