Digital Signal Processing

By Steven W. Smith, Ph.D.

- 1: The Breadth and Depth of DSP
- 2: Statistics, Probability and Noise
- 3: ADC and DAC
- 4: DSP Software
- 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
- 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
- 22: Audio Processing
- 23: Image Formation & Display
- 24: Linear Image Processing
- 25: Special Imaging Techniques
- 26: Neural Networks (and more!)
- 27: Data Compression
- 28: Digital Signal Processors
- 29: Getting Started with DSPs
- 30: Complex Numbers
- 31: The Complex Fourier Transform
- 32: The Laplace Transform
- 33: The z-Transform
- 34: Explaining Benford's Law

Your laser printer will thank you!

Digital Signal Processing is one of the most powerful technologies that will shape science and
engineering in the twenty-first century. Revolutionary changes have already been made in a *broad* range of fields: communications, medical imaging, radar & sonar, high fidelity music
reproduction, and oil prospecting, to name just a few. Each of these areas has developed a *deep*
DSP technology, with its own algorithms, mathematics, and specialized techniques. This
combination of breath and depth makes it impossible for any one individual to master all of the
DSP technology that has been developed. DSP education involves two tasks: learning general
concepts that apply to the field as a whole, and learning specialized techniques for your
particular area of interest. This chapter starts our journey into the world of Digital Signal
Processing by describing the dramatic effect that DSP has made in several diverse fields. The revolution has begun.