| Portion of title |
Guide to digital signal processing |
| Portion of title |
Digital signal processing |
| Contents |
Part I. Foundations : -- 1. The Breadth and Depth of DSP -- 2. Statistics, Probability and Noise -- 3. ADC and DAC -- 4. DSP Software -- Part II. Fundamentals : -- 5. Linear Systems -- 6. Convolution -- 7. Properties of Convolution -- 8. The Discrete Fourier Transform -- 9. Applications of the DFT -- 10. Fourier Transform Properties -- 11. Fourier Transform Pairs -- 12. The Fast Fourier Transform -- 13. Continuous Signal Processing -- Part III. Digital Filters : -- 14. Introduction to Digital Filters -- 15. Moving Average Filters -- 16. Windowed-Sinc Filters -- 17. Custom Filters -- 18. FFT Convolution -- 19. Recursive Filters -- 20. Chebyshev Filters -- 21. Filter Comparison -- Part IV. Applications : -- 22. Audio Processing -- 23. Image Formation and Display -- 24. Linear Image Processing -- 25. Special Imaging Techniques -- 26. Neural Networks (and more!) -- 27. Data Compression -- Part V. Complex Techniques : -- 28. Complex Numbers -- 29. The Complex Fourier Transform -- 30. The Laplace Transform -- 31. The z-Transform. |
| Summary |
Table of contents: Foundations; Fundamentals; Digital filters; Applications; Complex techniques. |
| Summary |
Glossary. |
| Summary |
Index. |
| Summary |
Book review: This book was written for scientists and engineers in a wide variety of fields: physics, bioengineering, geology, oceanography, mechanical and electrical engineering, to name just a few. |
| Summary |
The goal is to present Digital Signal Processing in practical techniques while avoiding the barriers of detailed mathematics and abstract theory. |
| Summary |
To achieve this goal, three strategies were employed in writing this book: First, the techniques are explained, not simply proven to be true through mathematical derivations. |
| Summary |
While much of the mathematics is included, it is not used as the primary means of conveying the information. |
| Summary |
Nothing beats a few well written paragraphs supported by good illustrations. |
| Summary |
Second, complex numbers are treated as an advanced topic, something to be learned after the fundamental principles are understood. |
| Summary |
Chapters 1-29 explain all the basic techniques using only algebra, and in rare cases, a small amount of elementary calculus. |
| Summary |
Chapters 30-33 show how complex math extends the power of DSP, presenting techniques that cannot be implemented with real numbers alone. |
| Summary |
Third, very simple computer programs are used. |
| Summary |
Most DSP programs are written in C, Fortran, or a similar language. |
| Summary |
However, learning DSP has different requirements than using DSP. |
| Summary |
The student needs to concentrate on the algorithms and techniques, without being distracted by the quirks of a particular language. |
| Summary |
Power and flexibility aren't important; simplicity is critical. |
| Summary |
The programs in this book are written to teach DSP in the most straightforward way, with all other factors being treated as secondary. |
| Summary |
Good programming style is disregarded if it makes the program logic more clear. |
| General note | Includes index. |
| LCCN | 97080293 |
| ISBN | 0966017633 |
| ISBN | 9780966017632 |