This book provides a complete overview of the foundations of continuous-time systems, and introduces the "new circuit theory" of discrete-time systems. It looks at the concepts and analysis tools associated with signal spectra--focusing on periodic signals and the Discrete Fourier Transform, making readers aware of the capabilities of MATLAB. Topics include analysis techniques, frequency response, standard filters, spectral analysis, discrete-time signals and systems, IRR and FIR filter designs, and sampling strategies. For those involved in electrical, computer, and telecommunications engineering.
This comprehensive text on control systems is designed for undergraduate students pursuing courses in electronics and communication engineering, electrical and electronics engineering, telecommunication engineering, electronics and instrumentation engineering, mechanical engineering, and biomedical engineering. Appropriate for self-study, the book will also be useful for AMIE and IETE students. Written in a student-friendly readable manner, the book explains the basic fundamentals and concepts of control systems in a clearly understandable form. It is a balanced survey of theory aimed to provide the students with an in-depth insight into system behaviour and control of continuous-time control systems. All the solved and unsolved problems in this book are classroom tested, designed to illustrate the topics in a clear and thorough way. KEY FEATURES : Includes several fully worked-out examples to help students master the concepts involved. Provides short questions with answers at the end of each chapter to help students prepare for exams confidently. Offers fill in the blanks and objective type questions with answers at the end of each chapter to quiz students on key learning points. Gives chapter-end review questions and problems to assist students in reinforcing their knowledge.
Getting mixed signals in your signals and systems course? The concepts covered in a typical signals and systems course are often considered by engineering students to be some of the most difficult to master. Thankfully, Signals & Systems For Dummies is your intuitive guide to this tricky course, walking you step-by-step through some of the more complex theories and mathematical formulas in a way that is easy to understand. From Laplace Transforms to Fourier Analyses, Signals & Systems For Dummies explains in plain English the difficult concepts that can trip you up. Perfect as a study aid or to complement your classroom texts, this friendly, hands-on guide makes it easy to figure out the fundamentals of signal and system analysis. Serves as a useful tool for electrical and computer engineering students looking to grasp signal and system analysis Provides helpful explanations of complex concepts and techniques related to signals and systems Includes worked-through examples of real-world applications using Python, an open-source software tool, as well as a custom function module written for the book Brings you up-to-speed on the concepts and formulas you need to know Signals & Systems For Dummies is your ticket to scoring high in your introductory signals and systems course.
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 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.
This book is a self-contained introduction to the theory of signals and systems, which lies at the basis of many areas of electrical and computer engineering. In the seventy short ?glectures,?h formatted to facilitate self-learning and to provide easy reference, the book covers such topics as linear time-invariant (LTI) systems, the Fourier transform, the Laplace Transform and its application to LTI differential systems, state-space systems, the z-transform, signal analysis using MATLAB, and the application of transform techniques to communication systems. A wide array of technologies, including feedback control, analog and discrete-time fi lters, modulation, and sampling systems are discussed in connection with their basis in signals and systems theory. The accompanying CD-ROM includes applets, source code, sample examinations, and exercises with selected solutions.
Signals and Systems Made Ridiculously Simple presents the core concepts and applications of signal processing and linear system theory in a clear and concise format. Each chapter provides carefully selected illustrations and examples to make learning or relearning the material as simple as possible. This book is designed to serve as both a study guide and reference book on this fundamental subject. -- Back cover.
This textbook covers the fundamental theories of signals and systems analysis, while incorporating recent developments from integrated circuits technology into its examples. Starting with basic definitions in signal theory, the text explains the properties of continuous-time and discrete-time systems and their representation by differential equations and state space. From those tools, explanations for the processes of Fourier analysis, the Laplace transform, and the z-Transform provide new ways of experimenting with different kinds of time systems. The text also covers the separate classes of analog filters and their uses in signal processing applications. Intended for undergraduate electrical engineering students, chapter sections include exercise for review and practice for the systems concepts of each chapter. Along with exercises, the text includes MATLAB-based examples to allow readers to experiment with signals and systems code on their own. An online repository of the MATLAB code from this textbook can be found at github.com/springer-math/signals-and-systems.
This book is primarily intended for junior-level students who take the courses on ‘signals and systems’. It may be useful as a reference text for practicing engineers and scientists who want to acquire some of the concepts required for signal proce- ing. The readers are assumed to know the basics about linear algebra, calculus (on complex numbers, differentiation, and integration), differential equations, Laplace R transform, and MATLAB . Some knowledge about circuit systems will be helpful. Knowledge in signals and systems is crucial to students majoring in Electrical Engineering. The main objective of this book is to make the readers prepared for studying advanced subjects on signal processing, communication, and control by covering from the basic concepts of signals and systems to manual-like introduc- R R tions of how to use the MATLAB and Simulink tools for signal analysis and lter design. The features of this book can be summarized as follows: 1. It not only introduces the four Fourier analysis tools, CTFS (continuous-time Fourier series), CTFT (continuous-time Fourier transform), DFT (discrete-time Fourier transform), and DTFS (discrete-time Fourier series), but also illuminates the relationship among them so that the readers can realize why only the DFT of the four tools is used for practical spectral analysis and why/how it differs from the other ones, and further, think about how to reduce the difference to get better information about the spectral characteristics of signals from the DFT analysis.
