Signals and Systems: A Primer with MATLAB

Citation

Sadiku, M. N. O., Ali, W. H., & Musa, S. M. (2024). Signals and Systems: A Primer with MATLAB (2nd ed.). CRC Press.

Chapter Summary

The second edition has seven chapters and four appendices in about 470 pages. Every chapter follows the same pattern: an introduction, the theory in numbered sections, a section on applications, a section titled "Computing with MATLAB", then a summary, review questions and problems. CRC Press describes the book as a textbook for junior-level students in electrical and computer engineering, and says the main aim of the second edition is to make the first edition clearer while keeping its goal of presenting continuous-time and discrete-time signals and systems in a clearer, more interesting and easier way than other texts.

Chapter 1: Basic Concepts

At about 70 pages, the longest chapter. It defines signals and systems, classifies signals, introduces the basic continuous-time and discrete-time signals and the operations performed on them, and classifies systems. As in every chapter, the theory is followed by applications and MATLAB computation.

Chapter 2: Convolution

Introduces the impulse response and the convolution integral, works through graphical convolution and block-diagram representation, then turns to discrete-time convolution and block-diagram realisation.

Chapter 3: The Laplace Transform

Covers the definition and properties of the Laplace transform, its inverse and the transfer function, followed by applications. The Laplace transform comes before Fourier analysis in this book.

Chapter 4: Fourier Series

Develops the trigonometric and exponential Fourier series, their properties and the truncated complex Fourier series.

Chapter 5: The Fourier Transform

Defines the Fourier transform, its properties and inverse, and closes the theory with Parseval's theorem and a comparison of the Fourier and Laplace transforms.

Chapter 6: Discrete Fourier Transform

Moves to discrete time: the discrete-time Fourier transform and its properties, the discrete Fourier transform and the fast Fourier transform.

Chapter 7: z-Transform

The discrete-time counterpart of the Laplace transform: definition, region of convergence, properties and the inverse z-transform, with applications.

Appendices A–D

Mathematical formulas, complex numbers, an introduction to MATLAB, and answers to the odd-numbered problems.

Key Concepts

Chapters 1–2: Basic Concepts; Convolution

• Signal and system classification: sorting signals (for example, continuous or discrete time) and systems by their properties before analysing them.
• Impulse response: a system's output for an impulse input, which characterises the system completely.
• Convolution: the operation that gives the output of a linear time-invariant system from its input and impulse response, in continuous and discrete time.

Chapter 3: The Laplace Transform

• Transfer function: the ratio of output to input transforms, the main tool for analysing continuous-time systems.
• Inverse Laplace transform: recovering time-domain behaviour from a transform.

Chapters 4–5: Fourier Series; The Fourier Transform

• Fourier series: representing a periodic signal as a sum of sinusoids or complex exponentials.
• Fourier transform: the frequency-domain description of non-periodic signals.
• Parseval's theorem: equality of a signal's energy in the time and frequency domains.

Chapters 6–7: Discrete Fourier Transform; z-Transform

• DTFT, DFT and FFT: the discrete-time Fourier transform, its sampled finite version, and the fast algorithm for computing it.
• Region of convergence: the set of values of z for which a z-transform exists, needed to interpret it uniquely.

Critical Analysis

Strengths

• Consistent structure. Every chapter has the same sequence of theory, applications, MATLAB, summary, review questions and problems, which makes the book easy to navigate and to plan around.
• Computation built in. A "Computing with MATLAB" section in every chapter, plus an introductory MATLAB appendix, means students practise computing and plotting transforms alongside the hand methods.
• Short and focused. Seven chapters give a compact path through the standard transform toolkit, suitable for a one-semester course or for revision. Answers to odd-numbered problems support self-study.
• Experienced author. Sadiku is co-author, with Charles Alexander, of Fundamentals of Electric Circuits and has written many other engineering textbooks; the publisher's biography notes that he is an IEEE Life Fellow for contributions to computational electromagnetics and engineering education.

Limitations

• Narrow scope. The contents list shows no chapter on sampling, modulation or communication systems, filter design, state-space methods or feedback; topics that a broader signals-and-systems course includes must come from elsewhere.
• Uneven depth. Chapter 1 runs to about 70 pages. Apart from discrete-time sections in Chapters 1 and 2, the discrete-time material is concentrated in the last two chapters (about 90 pages together), while the Laplace and Fourier chapters on continuous time take about 170.
• Assumes the target reader. The publisher's stated audience is junior-level electrical and computer engineering students, so calculus, complex numbers and basic circuits can be expected as background; Appendix B on complex numbers and Appendix A on formulas help, but the book is not a first introduction to the mathematics.
• Tied to MATLAB. The computing sections use MATLAB throughout; readers without access to it will need to translate the examples into another tool.

Where It Fits in the Course

Within the signals, systems and control course, Sadiku, Ali and Musa offer a compact transform-methods primer. Oppenheim and Willsky's Signals and Systems is the standard full textbook for the core course, treating continuous and discrete time side by side and going on to sampling, modulation and an introduction to feedback; Sadiku is a shorter, more direct route through the same core and a good place for revision before or during that course. Allen Downey's Think DSP approaches the subject computationally through Python code and sound, and pairs well with Sadiku's hand methods for readers who want experiments rather than MATLAB exercises.

The control books build on what Sadiku teaches: Nise's Control Systems Engineering models and designs feedback systems with tools such as MATLAB and Simulink, and Sadiku's Chapter 3 on Laplace transforms and transfer functions is the most direct preparation for it. Åström and Murray's Feedback Systems, which covers state-space methods, and Craig's Introduction to Robotics come later and go well beyond this primer.

How to Use This Book

The book is for electrical and computer engineering students in their third year, or anyone who needs a short, structured course in transform methods. Readers should have calculus, complex numbers and an introductory circuits course; Appendices A and B gather the formulas and complex-number results the book uses.

A practical plan:

• Core: Chapters 1–3 in order. Convolution and the Laplace transform are used everywhere afterwards, especially in control.
• Frequency domain: Chapters 4–5. Work the comparison of Fourier and Laplace transforms in Chapter 5 carefully; it ties the two halves together.
• Discrete time: Chapters 6–7, which are essential for students heading towards digital signal processing.
• Skim or use as reference: the applications sections, depending on the course.

Do the MATLAB section of each chapter after the hand-worked examples and use it to check answers to problems. Read Appendix C first if MATLAB is new. Use the review questions as a quick self-test, then the problems, checking odd-numbered answers in Appendix D. For sampling, filter design or state-space methods, turn to a fuller signals-and-systems or control text.