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Herausgeber: John Wiley & Sons
Kategorie: Wissenschaft und neue Technologien
Sprache: Englisch

Beschreibung

A comprehensive and detailed treatment of the program SIMULINK® that focuses on SIMULINK® for simulations in Digital and Wireless Communications Modeling of Digital Communication Systems Using SIMULINK® introduces the reader to SIMULINK®, an extension of the widely-used MATLAB modeling tool, and the use of SIMULINK® in modeling and simulating digital communication systems, including wireless communication systems. Readers will learn to model a wide selection of digital communications techniques and evaluate their performance for many important channel conditions. Modeling of Digital Communication Systems Using SIMULINK® is organized in two parts. The first addresses Simulink® models of digital communications systems using various modulation, coding, channel conditions and receiver processing techniques. The second part provides a collection of examples, including speech coding, interference cancellation, spread spectrum, adaptive signal processing, Kalman filtering and modulation and coding techniques currently implemented in mobile wireless systems. * Covers case examples, progressing from basic to complex * Provides applications for mobile communications, satellite communications, and fixed wireless systems that reveal the power of SIMULINK modeling * Includes access to useable SIMULINK® simulations online * All models in the text have been updated to R2018a; only problem sets require updating to the latest release by the user Covering both the use of SIMULINK® in digital communications and the complex aspects of wireless communication systems, Modeling of Digital Communication Systems UsingSIMULINK® is a great resource for both practicing engineers and students with MATLAB experience.

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Leseprobe

Cover

Title Page

Dedication

Preface

Scope

Organization of the Book

Chapter 1

Chapter 2

Chapter 3

Chapter 4

Chapter 5

Chapter 6

Chapter 7

Chapter 8

Chapter 9

Chapter 10

Chapter 11

Chapter 12

Chapter 13

About the Software

Acknowledgments

About the Companion Website

Abbreviations and Acronyms

Chapter 1: Getting Started With Simulink

1.1 Introduction

1.2 Starting a MATLAB Session

1.3 Simulink Block Libraries

1.4 Building a New Simulink Model

1.5 Executing the Simulink Model

1.6 Reconfiguring the Signal Block

1.7 Sample-Based Signals

1.8 Sending Data to Workspace

1.9 Using Model Explorer

1.10 Adding Labels to Figures

1.11 Selecting Model Configuration Parameters

1.12 Summary Discussion

Problems

Chapter 2: Sinusoidal Simulink Model

2.1 A First Simulink Model

2.2 Simulink Model of Sine Wave

2.3 Spectrum of a Sine Wave

2.4 Summary Discussion

Problems

Chapter 3: Digital Communications BER Performance in AWGN (BPSK and QPSK)

3.1 BPSK and QPSK Error Rate Performance in AWGN

3.2 Construction of a Simulink Model in Simple Steps

3.3 Comparison of Simulated and Theoretical BER

3.4 Alternate Simulink Model for BPSK

3.5 Frame-Based Simulink Model

3.6 QPSK Symbol Error Rate Performance

3.7 BPSK Fixed Point Performance

3.8 Summary Discussion

Appendix 3.A: Theoretical BER Performance of BPSK in AWGN

Problems

Chapter 4: Digital Communications BER Performance in AWGN (MPSK & QAM)

4.1 MPSK and QAM Error Rate Performance in AWGN

4.2 MPSK Simulink Model

4.3 BER for Other Alphabet Sizes

4.4 Fixed Point BER for MPSK

4.5 QAM Simulink Model

4.6 QAM BER for Other Alphabet Sizes Using Average Power

4.7 QAM BER Using Peak Power

4.8 Power Amplifier Constraint Using Peak Power Selection with QAM

4.9 Summary Discussion

Problems

Chapter 5: Digital Communications BER Performance in AWGN (FSK and MSK)

5.1 FSK and MSK Error Rate Performance in AWGN

5.2 BFSK Simulink Model

5.3 MFSK Simulink Model

5.4 MSK Simulink Model

5.5 MSK Power Spectrum

5.6 Summary Discussion

Problems

Chapter 6: Digital Communications BER Performance in AWGN (BPSK in Fading)

6.1 BPSK in Rayleigh and Rician Fading

6.2 BPSK BER Performance in Rayleigh Fading

6.3 BPSK BER Performance in Rician Fading

6.4 BPSK BER Performance in Rician Fading with Multipath

6.5 Summary Discussion

Appendix 6.A: Theoretical BER Performance of BPSK in Rayleigh Fading

Appendix 6.B: Theoretical BER Performance of BPSK in Rician Fading

Problems

Chapter 7: Digital Communications BER Performance in AWGN (FSK in Fading)

7.1 FSK in Rayleigh and Rician Fading

7.2 BFSK BER Performance in Rayleigh Fading

7.3 MFSK BER Performance in Rayleigh Fading

7.4 BFSK BER Performance in Rician Fading

7.5 BFSK BER Performance in Rician Fading with Multipath

7.6 Summary Discussion

Appendix 7A: Theoretical BER Performance of FSK in Rayleigh and Rician Fading

Problems

Chapter 8: Digital Communications BER Performance (STBC)

8.1 Digital Modulations in Rayleigh Fading With STBC

8.2 BPSK BER in Rayleigh Fading with STBC

8.3 QAM BER in Rayleigh Fading with STBC

8.4 Summary Discussion

Appendix 8A: Space–Time Block Coding for BPSK

Appendix 8B: Space–Time Block Coding for 16-QAM

Problems

Chapter 9: Digital Communications BER Performance in AWGN (Block Coding)

9.1 Digital Communications with Block Coding in AWGN

9.2 BER Performance of BPSK in AWGN with a Binary BCH Block Code

9.3 BER Performance of BPSK in AWGN with a Hamming Code

9.4 BER Performance of BPSK in AWGN with a Golay(24,12) Block Code

9.5 BER Performance of FSK in AWGN with Reed-Solomon Code

9.6 BER Performance of QAM in AWGN with Reed-Solomon Coding

9.7 Summary Discussion

Problems

Chapter 10: Digital Communications BER Performance in AWGN (Block Coding and Fading)

10.1 Digital Communications with Block Coding in Fading

10.2 BER Performance of BPSK in Rayleigh Fading with Interleaving and a BCH Block Code

10.3 BER Performance of BFSK in Rayleigh Fading with Interleaving and a Golay(24,12) Block Code

10.4 BER Performance of 32-FSK in Rayleigh Fading with Interleaving and a Reed-Solomon(31,15) Block Code

10.5 BER Performance of 16-QAM in Rayleigh Fading with Interleaving and a Reed-Solomon(15,7) Block Code

10.6 BER Performance of 16-QAM in Rayleigh and Rician Fading with Interleaving and a Reed-Solomon(15,7) Block Code

10.7 BER Performance of BPSK in Rayleigh Fading with Interleaving and a BCH Block Code and Alamouti STBC

10.8 BER Performance of BFSK in Rayleigh Fading with Interleaving and a Golay(24,12) Block Code and Alamouti STBC

10.9 BER Performance of 32-FSK in Rayleigh Fading with Interleaving and a Reed-Solomon(31,15) Block Code and Alamoutix STBC

10.10 BER Performance of 16-QAM in Rayleigh Fading with Interleaving and a Reed-Solomon (15,7) Block Code and Alamouti STBC

10.11 Summary Discussion

Problems

Chapter 11: Digital Communications BER Performance in AWGN and Fading (Convolutional Coding)

11.1 Digital Communications with Convolutional Coding in AWGN and Fading

11.2 BER Performance of Convolutional Coding and BPSK in AWGN

11.3 BER Performance of Convolutional Coding and BPSK in AWGN and Rayleigh Fading with Interleaving (Soft- and Hard-Decision Decoding)

11.4 BER Performance of Convolutional Coding and BPSK and Alamouti STBC in Rayleigh Fading with Interleaving

11.5 Summary Discussion

Problems

Chapter 12: Adaptive Equalization in Digital Communications

12.1 Adaptive Equalization

12.2 BER Performance of BPSK in Dispersive Multipath Channel Using an LMS Linear Equalizer

12.3 BER Performance of BPSK in Dispersive Multipath Channel Using an LMS Linear Equalizer From the Simulink Library

12.4 BER Performance of QPSK in a channel with ISI Using an LMS Linear Equalizer

12.5 BER Performance of BPSK in Dispersive Multipath Channel Using a Decision Feedback Equalizer

12.6 BER Performance of BPSK in Rayleigh Fading Multipath Channel Using an RLS Equalizer

12.7 Summary Discussion

Problems

Chapter 13: Simulink Examples

13.1 Linear Predictive Coding (LPC) for Speech Compression

13.2 RLS Interference Cancellation

13.3 Spread Spectrum

13.4 Antenna Nulling

13.5 Kalman Filtering

13.6 Orthogonal Frequency Division Multiplexing

13.7 Turbo Coding with BPSK

Appendix A: Principal Simulink Blocks used in Chapters 1–13

A.A.1 Sources (Figure A.1)

A.A.2 Sinks (Figure A.2)

A.A.3 Modulations (Figure A.3)

A.A.4 Channels (Figure A.4)

A.A.5 Error Control Coding (Figure A.5)

A.A.6 Signal Processing (Figure A.6)

A.A.7 Statistics (Figure A.7)

A.A.8 Special Blocks (Figure A.8)

Appendix B: Further Reading

Index

End User License Agreement

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Guide

Cover

Table of Contents

Preface

Begin Reading

List of Illustrations

Figure 1.1

Figure 1.2

Figure 1.3

Figure 1.4

Figure 1.5

Figure 1.6

Figure 1.7

Figure 1.8

Figure 1.9

Figure 1.10

Figure 1.11

Figure 1.12

Figure 1.13

Figure 1.14

Figure 1.15

Figure 1.16

Figure 1.17

Figure 1.18

Figure 1.19

Figure 1.20

Figure 1.21

Figure 1.22

Figure 1.23

Figure 1.24

Figure 1.25

Figure 1.26

Figure 1.27

Figure 1.28

Figure 1.29

Figure 1.30

Figure 1.31

Figure 2.1

Figure 2.2

Figure 2.3

Figure 2.4

Figure 2.5

Figure 2.6

Figure 2.7

Figure 2.8

Figure 2.9

Figure 2.10

Figure 2.11

Figure 2.12

Figure 2.13

Figure 2.14

Figure 3.1

Figure 3.2

Figure 3.3

Figure 3.4

Figure 3.5

Figure 3.6

Figure 3.7

Figure 3.8

Figure 3.9

Figure 3.10

Figure 3.11

Figure 3.12

Figure 3.13

Figure 3.14

Figure 3.15

Figure 3.16

Figure 3.17

Figure 3.18

Figure 3.19

Figure 3.20

Figure 3.21

Figure 3.22

Figure 3.23

Figure 3.24

Figure 3.25

Figure 3.26

Figure 3.27

Figure 3.28

Figure 3.29

Figure 3.30

Figure 3.31

Figure 3.32

Figure 3.33

Figure 3.34

Figure 3.35

Figure 3.36

Figure 3.37

Figure P.3.1

Figure P.3.2

Figure P.3.3

Figure 4.1

Figure 4.2

Figure 4.3

Figure 4.4

Figure 4.5

Figure 4.6

Figure 4.7

Figure 4.8

Figure 4.9

Figure 4.10

Figure 4.11

Figure 4.12

Figure 4.13

Figure 4.14

Figure 4.15

Figure 4.16

Figure 4.17

Figure 4.18

Figure 4.19

Figure 5.1

Figure 5.2

Figure 5.3

Figure 5.4

Figure 5.5

Figure 5.6

Figure 5.7

Figure 5.8

Figure 5.9

Figure 5.10

Figure 5.11

Figure 5.12

Figure 5.13

Figure 5.14

Figure 5.15

Figure 5.16

Figure 5.17

Figure 5.18

Figure 5.19

Figure 6.1

Figure 6.2

Figure 6.3

Figure 6.4

Figure 6.5

Figure 6.6

Figure 6.7

Figure 6.8

Figure 6.9

Figure 6.10

Figure 6.11

Figure 6.12

Figure 6.13

Figure 6.14

Figure 6.15

Figure 6.16

Figure 6.17

Figure P.6.1

Figure 7.1

Figure 7.2

Figure 7.3

Figure 7.4

Figure 7.5

Figure 7.6

Figure 7.7

Figure 7.8

Figure 7.9

Figure 7.10

Figure P.7.1

Figure 8.1

Figure 8.2

Figure 8.3

Figure 8.4

Figure 8.5

Figure 8.6

Figure 8.7

Figure 8.8

Figure 8.A.1

Figure 9.1

Figure 9.2

Figure 9.3

Figure 9.4

Figure 9.5

Figure 9.6

Figure 9.7

Figure 9.8

Figure 9.9

Figure 9.10

Figure 9.11

Figure 9.12

Figure 9.13

Figure 9.14

Figure 9.15

Figure 9.16

Figure 10.1

Figure 10.2

Figure 10.3

Figure 10.4

Figure 10.5

Figure 10.6

Figure 10.7

Figure 10.8

Figure 10.9

Figure 10.10

Figure 10.11

Figure 10.12

Figure 10.13

Figure 10.14

Figure 10.15

Figure 10.16

Figure 10.17

Figure 10.18

Figure 10.19

Figure 10.20

Figure 10.21

Figure 10.22

Figure 11.1

Figure 11.2

Figure 11.3

Figure 11.4

Figure 11.5

Figure 11.6

Figure 11.7

Figure 11.8

Figure 11.9

Figure 11.10

Figure 11.11

Figure 11.12

Figure 11.13

Figure 11.14

Figure P.11.1

Figure 12.1

Figure 12.2

Figure 12.3

Figure 12.4

Figure 12.5

Figure 12.6

Figure 12.7

Figure 12.8

Figure 12.9

Figure 12.10

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Figure 12.13

Figure 12.14

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Figure 12.21

Figure 12.22

Figure 12.23

Figure 12.24

Figure 12.25

Figure 12.26

Figure 12.27

Figure 12.28

Figure 12.29

Figure 12.30

Figure 12.31

Figure 12.32

Figure 13.1

Figure 13.2

Figure 13.3

Figure 13.4

Figure 13.5

Figure 13.6

Figure 13.7

Figure 13.8

Figure 13.9

Figure 13.10

Figure 13.11

Figure 13.12

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Figure 13.53

Figure 13.54

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Figure 13.56

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Figure 13.60

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Figure 13.81

Figure A.1

Figure A.2

Figure A.3

Figure A.4

Figure A.5

Figure A.6

Figure A.7

Figure A.8

List of Tables

Table 2.1

Table 3.1

Table 3.2

Table 9.1

Table 12.1

Table 12.2

Table 13.1

Table 13.2

Table 13.3

Table 13.4

Table 13.5

Table 13.6

MODELING OF DIGITAL COMMUNICATION SYSTEMS USING SIMULINK®

ARTHUR A. GIORDANO & ALLEN H. LEVESQUE

Published by John Wiley & Sons, Inc., Hoboken, New Jersey

Published simultaneously in Canada

MATLAB and Simulink are registered trademarks of The MathWorks, Inc. See www.mathworks.com trademarks for a list of additional trademarks. The MathWorks Publisher Logo identifies books that contain MATLAB® content. Used with permission. The MathWorks does not warrant the accuracy of the text or exercises in this book or in the software downloadable fromhttp://www.wiley.com/WileyCDA/WileyTitle/ productCd-047064477X.html andhttp://www.mathworks.com/matlabcentral/fileexchange/?term=authorid% 3A80973. The book's or downloadable software's use or discussion of MATLAB® software or related products does not constitute endorsement or sponsorship by The MathWorks of a particular use of the MATLAB® software or related products.

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Library of Congress Cataloging-in-Publication Data:

Giordano, Arthur A. (Arthur Anthony), 1941-

Modeling of digital communications systems using Simulink / Arthur A. Giordano & Allen H. Levesque.

pages cm

Includes bibliographical references and index.

ISBN 978-1-118-40005-0 (cloth)

1. Digital communications–Computer simulation. 2. SIMULINK. I. Levesque, Allen H. II. Title.

TK5102.83.G56 2015

621.3820285′53--dc23

2014042283

To our families, especially Diane and Barbara

Preface

This book is designed to introduce the communications systems engineer to the use of The MathWorks® Simulink®1 for modeling and evaluating the performance of digital communications systems. Simulink is a block-oriented modeling tool that utilizes well-tested MATLAB® code to enable rapid development of simulations for communication systems modeling. This block-oriented approach obviates the need for writing new software routines. The Simulink library provides an extensive array of MathWorks-verified blocks available for assembling any specific model. Upon gaining facility with the use of Simulink, the user will have a robust engineering tool for estimating communication systems performance in instances where analytic results are unavailable, such as nonlinear systems or time-varying channels.

Scope

This book introduces the reader to Simulink, an extension of the widely-used MATLAB2 modeling tool, and the use of Simulink in modeling and simulating digital communication systems, including wireless communications systems. In contrast with other books that treat MATLAB in depth but treat Simulink only at an introductory level, this book enables the communication systems engineer to learn and use the extensive capabilities of Simulink to model a wide selection of digital communications systems and evaluate their performance for many important channel conditions.

The reader is expected to have an understanding of MATLAB and its environment. It is also expected that the reader has a basic knowledge of digital communications including modulation, coding, and channel models, digital signal processing (DSP) such as digital filtering and Fourier transforms and statistical communications. The book is not intended to be a substitute for a course in digital communications but can be a valuable accompaniment to such a course. The presentation in this text is designed to allow the user to gain familiarity with basic Simulink tools, enabling rapid construction of useful communications systems models rather than providing comprehensive Simulink training currently available from The MathWorks.

Another feature of Simulink, not treated in this book, is Simulink's capability to develop a model, produce C/C++ code and migrate the model for incorporation in an field-programmable gate array (FPGA) or DSP devices. The MathWorks Corporation provides training for this capability.

Organization of the Book

The book is organized in two parts. The first 12 chapters address Simulink models of digital communication systems using various modulation, coding, channel type, and receiver processing techniques. These chapters include theoretical results for known conditions, when available, and simulated results in other cases. Problem sets at the end of each chapter accompany topics to be emphasized. Chapter 13 provides an extensive collection of examples designed to acquaint the reader with applications that reveal the power of Simulink modeling. Appendix A summarizes principal Simulink blocks used in chapters 1–13. Appendix B provides a list of references for further reading on MATLAB and Simulink.

Chapter 1

In this chapter, the fundamentals of developing a Simulink model and its relationship to MATLAB are described. Screens encountered in a typical MATLAB session are presented.3 The Simulink library blocks are identified with a focus on the Communications System Toolbox and the DSP System Toolbox.

Chapter 2

This chapter is intended to introduce the user to the first and simplest Simulink model associated with a sinusoidal waveform. Block parameters are identified, the simulation is performed and outputs are sent to the Workspace. Blocks that display data and scopes showing waveforms are employed. A Fast Fourier Transform (FFT) block is used to compute the spectrum and compare with a sinusoid's known spectrum. Two blocks are used to determine the spectrum including a spectrum analyzer that has multiple spectrum settings. Commonly used math blocks are also incorporated into the Simulink model.

Chapter 3

This chapter introduces several topics in Simulink based on binary phase shift keying (BPSK) and quadrature phase shift keying (QPSK) modulations. Communications blocks for BPSK and QPSK are utilized along with communications channel blocks identified as additive white Gaussian noise (AWGN) and Gaussian noise. BPSK and QPSK bit error rate (BER) performance is simulated and compared with the corresponding theoretical BER results. Use of the bertool is shown to be a convenient technique to obtain BER performance over a range of bit energy to noise spectral density values. Sample-based and frame-based computations are presented where it is seen that frame-based computations are vector based and provide faster computation. The chapter concludes with Simulink computations employing fixed-point arithmetic.

Chapter 4

This chapter continues the development of Simulink models for coherent modulations including multi-phase PSK (MPSK) and quadrature amplitude modulation (QAM). Simulink modeling of BER performance for MPSK using floating- and fixed-point arithmetic is obtained for various alphabet sizes. Simulink modeling of QAM BER is performed for both average and peak power conditions, again with various alphabet sizes. Using an example of QAM signaling in conjunction with a nonlinear power amplifier highlights the power of Simulink to model a communication system and determine its performance in a case where theoretical results are not available.

Chapter 5

This chapter continues the development of Simulink models to determine simulated BER results focusing on binary frequency shift keying (BFSK), M-ary frequency shift keying (MFSK), minimum shift keying (MSK), and Gaussian minimum shift keying (GMSK). Comparison of simulated and theoretical performance confirms the facility to reliably estimate performance. The ability of the spectrum analyzer to exhibit a wide selection of spectral estimation techniques and parameters is demonstrated. Spectral efficiencies of BFSK, 4-FSK, MSK, and GMSK are obtained.

Chapter 6

Prior chapters have introduced Simulink models to acquaint the reader and obtain confidence in the results from Simulink model development. This chapter presents several topics in Simulink based on BPSK modulation in fading channels. Specifically both Rayleigh and Rician fading channels are incorporated in the Simulink models and used to simulate BPSK BER performance under a variety of channel conditions. Comparisons of theoretical with simulated results are performed. Simulink models that introduce multipath allow BPSK BER performance to be readily estimated and are examples where BER performance is not easily obtained analytically.

Chapter 7

Chapter 7 continues the investigation of BER performance using Simulink models incorporating Rayleigh and Rician fading channels with FSK modulation and noncoherent detection. BER performance for Simulink models implementing MFSK in Rayleigh fading is determined for a selection of alphabet sizes. This chapter concludes with a Simulink model that investigates the BER performance of coherently detected FSK in a multipath channel with Rician fading.

Chapter 8

Use of diversity is a well-known technique for mitigating the loss in performance due to fading. Space time block coding (STBC) using multiple transmit and/or receive antennas can substantially improve BER performance in these instances. The Simulink models presented here incorporate STBC for compensating for BER degradation due to channel fading. Using STBC, BER performance for BPSK and QAM modulations in Rayleigh fading is determined where it is seen that Simulink obviates the need for theoretical results.

Chapter 9

Block error control coding is an important technique to enhance communication system performance. Simulink models for BPSK in AWGN are used to develop BER performance for operation with common block codes including Hamming, Golay, and Bose–Chadhuri–Hocquenghem (BCH). Simulink models are also developed for FSK and QAM with Reed-Solomon codes. A Simulink example is provided to demonstrate the degradation due to multipath with and without coding.

Chapter 10

This chapter presents topics in Simulink based on block error control coding in a fading channel. Simulink models employing Rayleigh fading are shown for BCH coding with BPSK, Golay coding with BFSK, Reed-Solomon coding with 32-FSK, and Reed-Solomon coding with 16-QAM. In each of these cases, an interleaver is introduced. A Simulink model is also developed for Rician fading and interleaving using Reed-Solomon coding with 16-QAM. A concluding section presents Simulink models for selected block codes and modulations with STBC and interleaving in Rayleigh fading.

Chapter 11

Convolutional coding is another technique utilized to enhance communications system performance. This chapter presents topics in Simulink incorporating convolutional error control coding in an AWGN and a fading channel. Simulink models are developed for computing BER performance of convolutional coding and BPSK in AWGN and Rayleigh fading using both hard- and soft-decision decoding. This chapter concludes with a Simulink model for determining BER performance of convolutional coding and BPSK with STBC and interleaving in Rayleigh fading.

Chapter 12

Adaptive equalization has been used extensively to compensate for the degradations from time- dispersive multipath channels. Simulink models, incorporating adaptive equalization for multipath mitigation, are developed for linear least mean square (LMS) equalizers with BPSK and QPSK, decision feedback equalizers (DEFs) with BPSK and recursive least squares (RLS) equalizers with BPSK. A final Simulink model in this chapter was developed using RLS equalization with BPSK in Rayleigh fading. Simulation is required in each of these cases and Simulink is the tool that achieves the desired results.

Chapter 13

This chapter provides several Simulink examples for a variety of individual applications. In particular Simulink models are developed for the following situations: Linear Predictive Coding (LPC) for speech compression, RLS interference cancellation, spread spectrum, antenna nulling of a single interferer, Kalman filtering, Orthogonal Frequency Division Multiplexing (OFDM), and Turbo Coding with BPSK. The choice of topics is meant to illustrate the multiplicity of applications that can be investigated using Simulink modeling.

About the Software

Simulink models for all of the cases presented in this book are available on a companion website, www.wiley.com/go/simulink. All of the models have been successfully executed in MATLAB 2014a. The website also provides Simulink models for the problem sets, and for instructors, answers to the problems can be obtained through the website.

The MathWorks™ is the leading developer of mathematical computing software for engineers and scientists. Founded in 1984, with headquarters in Natick, Massachusetts, USA. Simulink

is a block diagram environment for multidomain simulation and Model-Based Design. It supports simulation, automatic code generation, and continuous test and verification of embedded systems.

MATLAB is a high-level language and interactive environment for numerical computation, visualization, and programming. Computations are most generally performed using vector and/or matrix representations.

Matlab screens are Reprinted with permission from The MathWorks, Inc.

Acknowledgments

This book was made possible by the generous support from The MathWorks™, who provided multiple MATLAB®/Simulink® releases during the book's preparation. The MathWorks technical staff provided valuable help in identifying and correcting Simulink model issues and for this we are extremely grateful. MATLAB Central is also a significant source of user-developed Simulink models that often enable the developer to obtain a satisfactory resolution of a complex problem. We want to thank Dr. Michael Mulligan at The MathWorks™ for agreeing to support this undertaking. We want to especially thank The MathWorks™ for offering to include our work in The MathWorks Book Program and for granting permissions to reprint a number of copyrighted figures throughout the book.