Book Details : | |
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Language | English |

Pages | 666 |

Format | |

Size | 22.6 MB |

Digital Signal Processing A Practical Guide for Engineers and Scientists by Steven K. Smith | PDF Free Download.

- The Breadth and Depth of DSP
- Statistics. Probability and Noise
- ADC and DAC
- DSP Software
- Linear Systems
- Convolution
- Properties of Convolution
- The Discrete Fourier Transform
- Fourier Transform Properties
- The Fast Fourier Transform
- Continuous Signal Processing
- Applications of the DFT
- Fourier Transform Pairs
- Introduction to Digital Filters
- Moving Average Filters
- Windowed-Sinc Filters
- Custom Filters
- FFT Convolution
- Recursive Filters
- Chebyshev Filters
- Filter Comparison
- Audio Processing
- Special Imaging Techniques
- Data Compression
- Digital Signal Processors
- Image Formation and Display
- Linear Image Processing
- Neural Networks (and more!)
- Getting Started with DSPs
- Complex Numbers
- The Complex Fourier Transform
- The Laplace Transform
- The z-Transform

The technical world is changing very rapidly. In only 15 years, the power of personal computers has increased by a factor of nearly one-thousand.

By all accounts, it will increase by another factor of one-thousand in the next 15 years. This tremendous power has changed the way science and engineering are done, and there is no better example of this than digital signal processing.

In the early 1980s, DSP was taught as a graduate-level course in electrical engineering. A decade later, DSP had become a standard part of the undergraduate curriculum.

Today, DSP is a basic skill needed by scientists and engineers in many fields. Unfortunately, DSP education has been slow to adapt to this change.

Nearly all DSP textbooks are still written in the traditional electrical engineering style of detailed and rigorous mathematics.

DSP is incredibly powerful, but if you can't understand it, you can't use it! 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.

The goal is to present practical techniques while avoiding the barriers of detailed mathematics and abstract theory.

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.

While much of the mathematics is included, it is not used as the primary means of conveying the information.

Nothing beats a few well-written paragraphs supported by good illustrations. Second, complex numbers are treated as an advanced topic, something to be learned after the fundamental principles are understood.

Chapters 1-29 explain all the basic techniques using only algebra, and in rare cases, a small amount of elementary calculus.

Chapters 30-33 show how complex math extends the power of DSP, presenting techniques that cannot be implemented with real numbers alone.

Many would view this approach as heresy! Traditional DSP textbooks are full of complex math, often starting right from the first chapter.

Third, very simple computer programs are used. Most DSP programs are written in C, Fortran, or a similar language. However, learning DSP has different requirements than using DSP.

The student needs to concentrate on the algorithms and techniques, without being distracted by the quirks of a particular language.

Power and flexibility aren't important; simplicity is critical. The programs in this book are written to teach DSP in the most straightforward way, with all other factors being treated as secondary.

Good programming style is disregarded if it makes the program logic more clear. For instance:

- a simplified version of BASIC is used
- line numbers are included
- the only control structure used is the FOR-NEXT loop
- there are no IIO statements

This is the simplest programming style I could find. Some may think that this book would be better if the programs had been written in C. I couldn't disagree more.

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