Practical Signals Theory with MATLAB Applications


Book Description

Practical Signals Theory with MATLAB Applications is organized around applications, first introducing the actual behavior of specific signals and then using them to motivate the presentation of mathematical concepts. Tervo sequences the presentation of the major transforms by their complexity: first Fourier, then Laplace, and finally the z-transform. The goal is to help students who can’t visualize phenomena from an equation to develop their intuition and learn to analyze signals by inspection. Finally, most examples and problems are designed to use MATLAB, making the presentation more in line with modern engineering practice.




Signals and Systems Using MATLAB


Book Description

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




Signal and System Analysis Using MATLAB(R)


Book Description

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.




Statistical Signal Processing in Engineering


Book Description

A problem-solving approach to statistical signal processing for practicing engineers, technicians, and graduate students This book takes a pragmatic approach in solving a set of common problems engineers and technicians encounter when processing signals. In writing it, the author drew on his vast theoretical and practical experience in the field to provide a quick-solution manual for technicians and engineers, offering field-tested solutions to most problems engineers can encounter. At the same time, the book delineates the basic concepts and applied mathematics underlying each solution so that readers can go deeper into the theory to gain a better idea of the solution’s limitations and potential pitfalls, and thus tailor the best solution for the specific engineering application. Uniquely, Statistical Signal Processing in Engineering can also function as a textbook for engineering graduates and post-graduates. Dr. Spagnolini, who has had a quarter of a century of experience teaching graduate-level courses in digital and statistical signal processing methods, provides a detailed axiomatic presentation of the conceptual and mathematical foundations of statistical signal processing that will challenge students’ analytical skills and motivate them to develop new applications on their own, or better understand the motivation underlining the existing solutions. Throughout the book, some real-world examples demonstrate how powerful a tool statistical signal processing is in practice across a wide range of applications. Takes an interdisciplinary approach, integrating basic concepts and tools for statistical signal processing Informed by its author’s vast experience as both a practitioner and teacher Offers a hands-on approach to solving problems in statistical signal processing Covers a broad range of applications, including communication systems, machine learning, wavefield and array processing, remote sensing, image filtering and distributed computations Features numerous real-world examples from a wide range of applications showing the mathematical concepts involved in practice Includes MATLAB code of many of the experiments in the book Statistical Signal Processing in Engineering is an indispensable working resource for electrical engineers, especially those working in the information and communication technology (ICT) industry. It is also an ideal text for engineering students at large, applied mathematics post-graduates and advanced undergraduates in electrical engineering, applied statistics, and pure mathematics, studying statistical signal processing.




Noise and Vibration Analysis


Book Description

Noise and Vibration Analysis is a complete and practical guide that combines both signal processing and modal analysis theory with their practical application in noise and vibration analysis. It provides an invaluable, integrated guide for practicing engineers as well as a suitable introduction for students new to the topic of noise and vibration. Taking a practical learning approach, Brandt includes exercises that allow the content to be developed in an academic course framework or as supplementary material for private and further study. Addresses the theory and application of signal analysis procedures as they are applied in modern instruments and software for noise and vibration analysis Features numerous line diagrams and illustrations Accompanied by a web site at www.wiley.com/go/brandt with numerous MATLAB tools and examples. Noise and Vibration Analysis provides an excellent resource for researchers and engineers from automotive, aerospace, mechanical, or electronics industries who work with experimental or analytical vibration analysis and/or acoustics. It will also appeal to graduate students enrolled in vibration analysis, experimental structural dynamics, or applied signal analysis courses.




Signals and Systems with MATLAB Applications


Book Description

This text contains a comprehensive discussion of continuous and discrete time signals and systems with many examples from MATLAB--software used to write efficient, compact programs to solve electrical and computer engineering problems of varying complexity. Intended for junior- and senior-level electrical engineering students and for self-study by working professionals, it discusses Laplace transformation and circuit analysis, impulse response, Fourier series, Z transform, and the Discrete Fourier transform and FFT. Solutions to all exercises are included in this revised edition.




Digital Signal and Image Processing Using MATLAB


Book Description

This title provides the most important theoretical aspects of Image and Signal Processing (ISP) for both deterministic and random signals. The theory is supported by exercises and computer simulations relating to real applications. More than 200 programs and functions are provided in the MATLAB® language, with useful comments and guidance, to enable numerical experiments to be carried out, thus allowing readers to develop a deeper understanding of both the theoretical and practical aspects of this subject.




Digital Signal Processing Using MATLAB for Students and Researchers


Book Description

Quickly Engages in Applying Algorithmic Techniques to Solve Practical Signal Processing Problems With its active, hands-on learning approach, this text enables readers to master the underlying principles of digital signal processing and its many applications in industries such as digital television, mobile and broadband communications, and medical/scientific devices. Carefully developed MATLAB® examples throughout the text illustrate the mathematical concepts and use of digital signal processing algorithms. Readers will develop a deeper understanding of how to apply the algorithms by manipulating the codes in the examples to see their effect. Moreover, plenty of exercises help to put knowledge into practice solving real-world signal processing challenges. Following an introductory chapter, the text explores: Sampled signals and digital processing Random signals Representing signals and systems Temporal and spatial signal processing Frequency analysis of signals Discrete-time filters and recursive filters Each chapter begins with chapter objectives and an introduction. A summary at the end of each chapter ensures that one has mastered all the key concepts and techniques before progressing in the text. Lastly, appendices listing selected web resources, research papers, and related textbooks enable the investigation of individual topics in greater depth. Upon completion of this text, readers will understand how to apply key algorithmic techniques to address practical signal processing problems as well as develop their own signal processing algorithms. Moreover, the text provides a solid foundation for evaluating and applying new digital processing signal techniques as they are developed.







Digital Signal Processing with Matlab Examples, Volume 2


Book Description

This is the second volume in a trilogy on modern Signal Processing. The three books provide a concise exposition of signal processing topics, and a guide to support individual practical exploration based on MATLAB programs. This second book focuses on recent developments in response to the demands of new digital technologies. It is divided into two parts: the first part includes four chapters on the decomposition and recovery of signals, with special emphasis on images. In turn, the second part includes three chapters and addresses important data-based actions, such as adaptive filtering, experimental modeling, and classification.