10. 0 Digital Signal Processing

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Название10. 0 Digital Signal Processing
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_____ Notes _____

Chapter Contents

10.0 Digital Signal Processing

10.1 Digital Filters

10.1.1 Difference Equations

10.1.2 Z Transforms

10.1.3 FIR Filters

10.1.4 Impulse Response Design

10.1.5 Windowing

10.1.6 IIR Filters

10.1.7 Laplace Transform

10.1.8 Impulse Response

10.1.9 Higher Order Filters

10.1.10 Design by Synthesis:

10.2 Convolution

10.2.1 Zero Forcing Equalizer

Review Questions

For Further Research

10.0 Digital Signal Processing


This section will:

  • Review some basic digital filter theory

  • Examine FIR filters

  • Examine IIR filters

  • Show how to design a digital filter using the impulse response

  • Introduce convolution




The first demonstration of a simple DSP device was in the 1930’s, but the first commercial programmable device didn’t come on the market until 1979. Since then DSP has revolutionized communications systems design and applications.

DSP has several significant advantages over traditional analog technology:

  • Size and cost of digital ICs is falling

  • Compatible with other digital technologies: transmission, switching, computers

  • Can be programmable

  • Stable and accurate

  • Increased functionality

There are however some disadvantages. Since DSPs can perform more complex functions than other techniques, circuit designers need a good grasp of mathematics. Unfortunately, there are relatively few user-friendly development and debugging tools.

A Simple DSP System

From the above diagram, it should be evident that a telephony PCM codec is a DSP system.

In order to run real time applications, the DSP processor must be able to execute all of its functions within one sampling period of the input filters. Some applications, such as real time video processing are beyond the state of current technology. However, there are slow scan or stop motion video applications, which are receiving a great deal of attention.

Applications can be categorized by the time it takes to produce a useful result. Real time applications such as telephony, require the processing to take milliseconds or less. Near real-time applications may take seconds to respond, while others may take minutes, hours or even days.

Run Time


Real Time

Telephony [codecs, cellular phones]

Consumer audio [CDs, DAT, toys]

Medical [ECG]

Multimedia [video compression]

Radar signal processing

Near Real Time

Adaptive equalizers

Medical [CAT scan]

Cruse missile guidance

Voice & pattern recognition [machine vision]

Long Time

Satellite & deep space imaging

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