System Analysis And Signal Processing

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.

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.

This Third Edition of a proven text presents the most widely used techniques of signal and systems analysis with superb coverage of devices. Intended for junior and senior students with basic calculus, this text features a clear organization of topics beginning with convolution, then moves to unusually extensive coverage of Fourier transforms. There are generous examples of discrete system applications that students can easily follow. The second half of the text supplies broad coverage of one- and two-sided Laplace transforms and analysis of discrete signals and systems by means of the z-transform. Students will benefit from state space material that has been expanded and rearranged to present the discrete case first, as well as an expanded learning system including solutions to all exercises plus an expanded appendix table with easy access to frequently encountered mathematical relationships used in signal analysis.

Are you looking for: a clear and accessible introduction to 'signals and systems'? a text that integrates the use of MATLAB throughout and provides an introductory tutorial to the software? comprehensive coverage of both continuous and discrete-time signal processing? a book that will be useful for further study? If the answer to any of the above questions is 'Yes' then this is the ideal coursebook for you. System Analysis and Signal Processing provides a self-contained text suitable for students of 'signals and systems' and signal processing, from introductory to graduate level; it also serves as a useful companion for those studying network analysis and communications. Clear explanations and easy-to-follow examples using practical situations help to make this book one of the most accessible on the topic. This is the only book you will need on the subject. Key Features a readable and concise treatment of the essential topics, emphasizing physical interpretations the smooth introduction of relevant mathematics in context a broad subject coverage including sections on spectral estimation, digital filter design, network analysis, transforms, analogue filters, automatic control, correlators and the processing of narrow-band signals practical and straightforward design and analysis techniques examples and problems that can be solved with Versions 4 and 5 of the student edition of MATLAB well-designed end of chapter problems that contribute to the learningprocess FREE solutions manual available to adopting lecturers

This new, fully-revised edition covers all the major topics of digital signal processing (DSP) design and analysis in a single, all-inclusive volume, interweaving theory with real-world examples and design trade-offs. Building on the success of the original, this edition includes new material on random signal processing, a new chapter on spectral estimation, greatly expanded coverage of filter banks and wavelets, and new material on the solution of difference equations. Additional steps in mathematical derivations make them easier to follow, and an important new feature is the do-it-yourself section at the end of each chapter, where readers get hands-on experience of solving practical signal processing problems in a range of MATLAB experiments. With 120 worked examples, 20 case studies, and almost 400 homework exercises, the book is essential reading for anyone taking DSP courses. Its unique blend of theory and real-world practical examples also makes it an ideal reference for practitioners.

A compact overview on signals and systems, with emphasis on analysis of continuous and discrete systems in time domain. Frequency-domain analysis, transform analysis and state-space analysis are also discussed in detail. With abundant examples and exercises to facilitate learning, it is an ideal texts for graduate students and lecturers in signal processing, and communication engineering.