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Introductory textbook on the fundamental concepts of continuous-time and discrete-time signals and systems, self-contained for independent or combined teaching approaches. Includes a CD-ROM containing MATLAB code and various signals. Contains worked examples, homework problems (solutions for instructors online) and extensive illustrations. Suitable for undergraduates in electrical and computer engineering.
This book is intended for use in teaching undergraduate courses on continuous-time signals and systems in engineering (and related) disciplines. It has been used for several years for teaching purposes in the Department of Electrical and Computer Engineering at the University of Victoria and has been very well received by students. This book provides a detailed introduction to continuous-time signals and systems, with a focus on both theory and applications. The mathematics underlying signals and systems is presented, including topics such as: properties of signals, properties of systems, convolution, Fourier series, the Fourier transform, frequency spectra, and the bilateral and unilateral Laplace transforms. Applications of the theory are also explored, including: filtering, equalization, amplitude modulation, sampling, feedback control systems, circuit analysis, and Laplace-domain techniques for solving differential equations. Other supplemental material is also included, such as: a detailed introduction to MATLAB, a review of complex analysis, and an exploration of time-domain techniques for solving differential equations. Throughout the book, many worked-through examples are provided. Problem sets are also provided for each major topic covered.
Exploring signals and systems, this work develops continuous-time and discrete-time concepts, highlighting the differences and similarities. Two chapters deal with the Laplace transform and the Z-transform. Basic methods such as filtering, communication an
This introductory text assists students in developing the ability to understand and analyze both continuous and discrete-time systems. The authors present the most widely used techniques of signal and system analysis in a highly readable and understandable fashion. *Covers the most widely used techniques of signal and system analysis. *Separate treatment of continuous-time and discrete-time signals and systems. *Extensive treatment of Fourier analysis. *A flexible structure making the text accessible to a variety of courses. *Makes extensive use of mathematics in an engineering context. *Uses an abundance of examples to illustrate ideas and apply the theoretical results.
Signals and Systems Using MATLAB, Third Edition, features a pedagogically rich and accessible approach to what can commonly be a mathematically dry subject. Historical notes and common mistakes combined with applications in controls, communications and signal processing help students understand and appreciate the usefulness of the techniques described in the text. This new edition features more end-of-chapter problems, new content on two-dimensional signal processing, and discussions on the state-of-the-art in signal processing. - Introduces both continuous and discrete systems early, then studies each (separately) in-depth - Contains an extensive set of worked examples and homework assignments, with applications for controls, communications, and signal processing - Begins with a review on all the background math necessary to study the subject - Includes MATLAB® applications in every chapter
"Provides rigorous treatment of deterministic and random signals"--
The Symposium covered three major areas: adaptive control, identification and signal processing. In all three, new developments were discussed covering both theoretical and applications research. Within the subject area of adaptive control the discussion centred around the challenges of robust control design to unmodelled dynamics, robust parameter estimation and enhanced performance from the estimator, while the papers on identification took the theme of it being a bridge between adaptive control and signal processing. The final area looked at two aspects of signal processing: recursive estimation and adaptive filters.