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.

Signal and System Analysis using MATLAB(R) is a textbook for Electronic Engineering Students and Design Engineers that introduces the main Digital Signal Processing (DSP) techniques required to perform Signal and System Analysis MATLAB(R). The primary aim of this book is to provide the analytical knowledge and practical techniques required for signal and system analysis by extensive use of the MATLAB(R) program, which is necessary for studying Digital Signal Processing to degree level and higher. The concept behind the book is to combine both the theory of Digital Signal Processing and the practical implementation of the theory using MATLAB(R). The goal is that students will gain an understanding of both the underlying theoretical concepts and how to apply them to real world problems using MATLAB(R). The chapters have been designed to enable students to develop their skills further by applying MATLAB(R) to all (50) problems, (161) examples, (290) equations and (449) figures. Worked examples of problems are shown in the book, followed by problems for students for practice. According to Fourier theory, a periodic signal can be represented by a Fourier series that contains the sum of a series of sine or cosine functions (harmonics) plus a Direct-Current (DC) term. The Continuous-Time Fourier Transform (CT-FT) can be used for non-periodic signal and is the way to express in the frequency domain a signal that is given in the time domain. The Laplace Transform is used to analyse the LTIC (Linear Time Inversion Continuous) systems and simplifies algebraic operations. The theories discussed in detail include; Continuous Time Convolution, Sampling, Quantizing, Reconstruction, Fourier analysis of Discrete-Time Signal, Discrete-Time convolution, circle convolution and the Fast Fourier Transform (FFT). The Z-Transform is an operation that transfers a discrete-time signal from the time domain (t) into the complex frequency domain (Z), and is a valuable tool in the digital signal processing field. Finally we discuss the Road to Wavelet Theory and its principles. Wavelet transform is a reversible transform, that is, it allows to go backwards and forwards between the time-domain and frequency-domain.

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

Digital signal processing lies at the heart of the communications revolution and is an essential element of key technologies such as mobile phones and the Internet. This book covers all the major topics in digital signal processing (DSP) design and analysis, supported by MatLab examples and other modelling techniques. The authors explain clearly and concisely why and how to use digital signal processing systems; how to approximate a desired transfer function characteristic using polynomials and ratio of polynomials; why an appropriate mapping of a transfer function on to a suitable structure is important for practical applications; and how to analyse, represent and explore the trade-off between time and frequency representation of signals. An ideal textbook for students, it will also be a useful reference for engineers working on the development of signal processing systems.

Developed as a textbook for the laboratory part of the course Signals and Systems, this book introduces students to theory through analytical examples implemented in Matlab code. Thus every theoretical equation is accompanied by the corresponding code implementation. Instead of using big M-Files or author-written functions with comments, the commands are executed one-by-one at the Matlab command line and the results, dong with comments are given side-by side in two or three column tables. This is very helpful and popular to students in Electrical Engineering, since the nature of this course includes detailed mathematical derivations and demands a strong mathematical background.

"Provides rigorous treatment of deterministic and random signals"--

Drawing on the author's 25+ years of teaching experience, Signals and Systems: A MATLAB Integrated Approach presents a novel and comprehensive approach to understanding signals and systems theory. Many texts use MATLAB as a computational tool, but Alkin's text employs MATLAB both computationally and pedagogically to provide interactive, visual rein

Offering radar-related software for the analysis and design of radar waveform and signal processing, Radar Signal Analysis and Processing Using MATLAB provides a comprehensive source of theoretical and practical information on radar signals, signal analysis, and radar signal processing with companion MATLAB code. Aft

Signal Processing for Intelligent Sensors with MATLAB®, Second Edition once again presents the key topics and salient information required for sensor design and application. Organized to make it accessible to engineers in school as well as those practicing in the field, this reference explores a broad array of subjects and is divided into sections: Fundamentals of Digital Signal Processing, Frequency Domain Processing, Adaptive System Identification and Filtering, Wavenumber Sensor Systems, and Signal Processing Applications. Taking an informal, application-based approach and using a tone that is more engineer-to-engineer than professor-to-student, this revamped second edition enhances many of the features that made the original so popular. This includes retention of key algorithms and development methodologies and applications, which are creatively grouped in a way that differs from most comparable texts, to optimize their use. New for the Second Edition: Inclusion of more solved problems Web access to a large collection of MATLAB® scripts used to support data graphs presented throughout the book Additional coverage of more audio engineering, transducers, and sensor networking technology A new chapter on Digital Audio processing reflects a growing interest in digital surround sound (5.1 audio) techniques for entertainment, home theaters, and virtual reality systems New sections on sensor networking, use of meta-data architectures using XML, and agent-based automated data mining and control Serving dual roles as both a learning resource and a field reference on sensor system networks, this book progressively reveals digestible nuggets of critical information to help readers quickly master presented algorithms and adapt them to meet their requirements. It illustrates the current trend toward agile development of web services for wide area sensor networking and intelligent processing in the sensor system networks that are employed in homeland security, business, and environmental and demographic information systems.

Designed for a one-semester undergraduate course in continuous linear systems, Continuous Signals and Systems with MATLAB®, Second Edition presents the tools required to design, analyze, and simulate dynamic systems. It thoroughly describes the process of the linearization of nonlinear systems, using MATLAB® to solve most examples and problems. With updates and revisions throughout, this edition focuses more on state-space methods, block diagrams, and complete analog filter design. New to the Second Edition • A chapter on block diagrams that covers various classical and state-space configurations • A completely revised chapter that uses MATLAB to illustrate how to design, simulate, and implement analog filters • Numerous new examples from a variety of engineering disciplines, with an emphasis on electrical and electromechanical engineering problems Explaining the subject matter through easy-to-follow mathematical development as well as abundant examples and problems, the text covers signals, types of systems, convolution, differential equations,Fourier series and transform, the Laplace transform, state-space representations, block diagrams, system linearization, and analog filter design. Requiring no prior fluency with MATLAB, it enables students to master both the concepts of continuous linear systems and the use of MATLAB to solve problems.