Signals and Systems (The Oxford Series in Electrical and Computer Engineering)
In Signals and Systems, Sanjit Mitra addresses the question: What are the core concepts that undergraduate students need to learn in order to successfully continue their studies in the field? Straightforward, easy-to-understand, and engaging, Signals and Systems enables students to focus on essential material by avoiding artificial signals and systems that they will never encounter in their professional careers.
Why Read This Book
You will learn the core theory and practical techniques that bridge classroom signals-and-systems concepts to real-world DSP applications, from filtering and FFTs to wavelets and adaptive methods. Mitra emphasizes intuitive, application-driven examples (audio, speech, radar, communications) so you can move quickly from analysis to implementation.
Who Will Benefit
Undergraduate and early graduate electrical/computer engineers or DSP practitioners who want a clear, application-focused foundation to analyze, design, and implement signal-processing systems.
Level: Intermediate — Prerequisites: Single-variable calculus, basic differential equations, introductory linear algebra, and elementary complex numbers; basic probability recommended for later chapters on random processes.
Key Takeaways
- Analyze continuous- and discrete-time signals and LTI systems using time- and frequency-domain transforms
- Design and implement FIR and IIR digital filters and understand their stability and structure
- Apply sampling, reconstruction, and multirate techniques including polyphase and decimation/interpolation
- Compute and use DFT/FFT efficiently for spectral analysis and practical algorithm design
- Use wavelets and filter-bank concepts for time-frequency analysis and signal compression
- Apply principles of random processes, spectral estimation, and adaptive filtering to noise-limited systems
Topics Covered
- 1. Introduction to Signals and Systems; basic signal models and units
- 2. Analysis of Continuous-Time Signals and Systems
- 3. Fourier Series and Fourier Transform for Continuous-Time Signals
- 4. Laplace Transform and System Function
- 5. Sampling Theorem and Reconstruction
- 6. Discrete-Time Signals and Systems; Convolution and LTI Properties
- 7. Z-Transform and Discrete-Time System Analysis
- 8. Discrete-Time Fourier Transform, DFT and FFT Algorithms
- 9. Digital Filter Structures; FIR and IIR Design Methods
- 10. Multirate Signal Processing and Filter Banks
- 11. Wavelets and Time–Frequency Techniques
- 12. Statistical Signal Processing and Spectral Estimation
- 13. Adaptive Filtering and Practical Algorithms (LMS, RLS)
- 14. Applications: Audio/Speech, Radar, and Communications Systems
- 15. Implementation Issues and Case Studies
Languages, Platforms & Tools
How It Compares
Compared with Oppenheim & Willsky's Signals and Systems (more theoretical) and Proakis & Manolakis' DSP (more algorithmic), Mitra strikes a balance with practical, application-oriented exposition and clearer DSP algorithm coverage.
