Digital Filters and Signal Processing: With MATLAB® Exercises
Digital Filters and Signal Processing, Third Edition ... with MATLAB Exercises presents a general survey of digital signal processing concepts, design methods, and implementation considerations, with an emphasis on digital filters. It is suitable as a textbook for senior undergraduate or first-year graduate courses in digital signal processing. While mathematically rigorous, the book stresses an intuitive understanding of digital filters and signal processing systems, with numerous realistic and relevant examples. Hence, practicing engineers and scientists will also find the book to be a most useful reference.
The Third Edition contains a substantial amount of new material including, in particular, the addition of MATLAB exercises to deepen the students' understanding of basic DSP principles and increase their proficiency in the application of these principles. The use of the exercises is not mandatory, but is highly recommended.
Other new features include: normalized frequency utilized in the DTFT, e.g., X(ejomega); new computer generated drawings and MATLAB plots throughout the book; Chapter 6 on sampling the DTFT has been completely rewritten; expanded coverage of Types I-IV linear-phase FIR filters; new material on power and doubly-complementary filters; new section on quadrature-mirror filters and their application in filter banks; new section on the design of maximally-flat FIR filters; new section on roundoff-noise reduction using error feedback; and many new problems added throughout.
Why Read This Book
You will learn how to design, analyze, and implement practical digital filters and signal-processing systems with an emphasis on intuition and realistic examples; the third edition pairs that theory with hands-on MATLAB exercises so you can immediately test designs and algorithms. If you want a compact, application-focused bridge between classroom theory and engineering practice—especially for filtering, spectral analysis, and adaptive methods—this book delivers clear explanations and usable MATLAB code.
Who Will Benefit
Senior undergraduate or first-year graduate students in electrical engineering and practicing engineers working on audio/speech, radar, or communications who need practical digital-filter design, spectral-analysis, and MATLAB-based implementation guidance.
Level: Intermediate — Prerequisites: Undergraduate background in signals and linear systems (Fourier and z-transforms), basic calculus and linear algebra; introductory probability is helpful for statistical sections; basic familiarity with MATLAB or numerical computing is recommended.
Key Takeaways
- Design classic FIR and IIR digital filters using a variety of windowing, frequency-sampling, and optimization methods.
- Implement and test filters, FFT-based algorithms, and spectral-analysis routines using MATLAB exercises and example code.
- Analyze filter structures, finite-word-length effects, numerical stability, and practical implementation trade-offs.
- Apply adaptive filtering techniques (e.g., LMS) to problems such as noise cancellation and system identification.
- Perform spectral analysis (including FFT methods and windowing) and link time-domain filter design to frequency-domain performance.
- Adapt signal-processing methods to application areas such as audio/speech processing, radar signal processing, and communications.
Topics Covered
- Introduction and overview of digital signal processing
- Review of discrete-time signals and linear time-invariant systems
- Transforms for discrete-time signals: z-transform and DTFT
- Sampling, aliasing, and discrete-time sampling theory
- FIR filter design: window methods and frequency sampling
- IIR filter design: analog prototypes, bilinear transform, and stability
- Filter structures, implementation issues, and finite-word-length effects
- FFT algorithms and efficient spectral analysis
- Windowing, power spectral estimation, and parametric spectral methods
- Adaptive filtering: LMS algorithms and practical considerations
- Multirate and decimation/interpolation techniques
- Statistical signal processing and estimation basics
- Applications: audio/speech processing, radar and communications examples
- MATLAB exercises and worked examples
- Advanced topics and emerging methods (including an introduction to wavelets)
Languages, Platforms & Tools
How It Compares
Covers similar classroom material to Oppenheim & Schafer's Discrete-Time Signal Processing and Proakis & Manolakis's DSP texts, but Jackson is more filter-centric, more application-oriented, and includes MATLAB exercises for hands-on learning.
