Signals and Systems Primer with MATLAB |
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| Author:
| Poularikas, Alexander D. |
| Series title: | Electrical Engineering and Applied Signal Processing Ser. |
| ISBN: | 978-1-315-22184-7 |
| Publication Date: | Oct 2018 |
| Publisher: | Taylor & Francis Group
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| Imprint: | CRC Press |
| Book Format: | Digital (delivered electronically) |
| List Price: | USD $140.00USD $210.00USD $155.00 |
Book Description:
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Signals and Systems Primer with MATLAB® equally emphasizes the fundamentals of both analog and digital signals and systems. To ensure insight into the basic concepts and methods, the text presents a variety of examples that illustrate a wide range of applications, from microelectromechanical to worldwide communication systems. It also provides MATLAB functions and procedures for practice and verification of these concepts. Taking a pedagogical approach, the author builds a...
More DescriptionSignals and Systems Primer with MATLAB® equally emphasizes the fundamentals of both analog and digital signals and systems. To ensure insight into the basic concepts and methods, the text presents a variety of examples that illustrate a wide range of applications, from microelectromechanical to worldwide communication systems. It also provides MATLAB functions and procedures for practice and verification of these concepts.
Taking a pedagogical approach, the author builds a solid foundation in signal processing as well as analog and digital systems. The book first introduces orthogonal signals, linear and time-invariant continuous-time systems, discrete-type systems, periodic signals represented by Fourier series, Gibbs's phenomenon, and the sampling theorem. After chapters on various transforms, the book discusses analog filter design, both finite and infinite impulse response digital filters, and the fundamentals of random digital signal processing, including the nonparametric spectral estimation. The final chapter presents different types of filtering and their uses for random digital signal processing, specifically, the use of Wiener filtering and least mean squares filtering.
Balancing the study of signals with system modeling and interactions, this text will help readers accurately develop mathematical representations of systems.