Signal Processing for Systems: Theory and Design (Wiley Series in Telecommunications and Signal Processing)
An Instructor's Manual presenting detailed solutions to all the problems in the book is available from the Wiley editorial department.
Why Read This Book
You should read this book if you want a rigorous, system-oriented treatment of discrete-time signal processing that connects theory to practical design choices (filter structures, realization forms, and implementation issues). It balances mathematical foundations with engineering design examples, so you will learn both how and why common DSP systems are built the way they are.
Who Will Benefit
Graduate students and practicing DSP engineers who need a thorough, design-focused treatment of discrete-time systems, filter realizations, and state-space methods for real-world DSP system design.
Level: Intermediate — Prerequisites: Undergraduate-level signals & systems and basic linear algebra; familiarity with z-transform, Fourier methods, and elementary digital filter concepts.
Key Takeaways
- Analyze discrete-time LTI systems using z-transforms and state-space representations.
- Design and compare FIR and IIR filter structures and realizations for stability, numerical behavior, and implementation cost.
- Evaluate frequency-response, stability margins, and the impact of quantization on system performance.
- Apply state-space methods to multirate and multi-input/multi-output DSP system design.
- Translate theoretical designs into practical implementations and trade off complexity, precision, and performance.
Topics Covered
- 1. Introduction and overview of signal processing systems
- 2. Discrete-time signals and the z-transform
- 3. Linear time-invariant systems and frequency response
- 4. State-space models for discrete-time systems
- 5. FIR filter design and realizations
- 6. IIR filter design and structures
- 7. Numerical issues and finite-precision effects
- 8. Multirate systems and decimation/interpolation
- 9. Implementation considerations and system-level design
- 10. Examples, design case studies, and exercise solutions
Languages, Platforms & Tools
How It Compares
Covers system-level and state-space design more than Oppenheim & Schafer's Discrete-Time Signal Processing (which is the canonical DSP algorithm text) and is more design-oriented than Proakis & Manolakis, which is broader on algorithms and communications applications.
