Lably
Skip to content

Digital-to-analog converter

Device that converts a digital signal into an analog signal

  • 11 min read
  • 5 chapters
Cirrus Logic CS4382 - 8-channel DAC from Sound Blaster X-Fi
Chepry 💬 ( Andrzej Barabasz ) 📷 🇵🇱 · CC BY-SA 3.0

Related on Lably

Through Electronics, Binary number and Voltage

DACs are commonly used in music players to convert digital data streams into analog audio signals. They are also used in televisions and mobile phones to convert digital video data into analog video signals. These two applications use DACs at opposite ends of the frequency/resolution trade-off. The audio DAC is a low-frequency, high-resolution type, while the video DAC is a high-frequency low- to medium-resolution type.

There are several DAC architectures; the suitability of a DAC for a particular application is determined by figures of merit, including: resolution, maximum sampling frequency and others. Digital-to-analog conversion can degrade a signal, so a DAC should be specified that has insignificant errors in terms of the application.

Due to the complexity and the need for precisely matched components, all but the most specialized DACs are implemented as integrated circuits (ICs). These typically take the form of metal–oxide–semiconductor (MOS) mixed-signal integrated circuit chips that integrate both analog and digital circuits.

Discrete DACs (circuits constructed from multiple discrete electronic components instead of a packaged IC) would typically be extremely high-speed, low-resolution, power-hungry types, as used in military radar systems. Very high-speed test equipment, especially sampling oscilloscopes, may also use discrete DACs.

Overview

A DAC converts an abstract finite-precision number (usually a fixed-point binary number) into a physical quantity (e.g., a voltage or a pressure). In particular, DACs are often used to convert finite-precision time series data to a continually varying physical signal.

Provided that a signal's bandwidth meets the requirements of the Nyquist–Shannon sampling theorem (i.e., a baseband signal with bandwidth less than the Nyquist frequency) and was sampled with infinite resolution, the original signal can theoretically be reconstructed from the sampled data. However, an ADC's filtering can't entirely eliminate all frequencies above the Nyquist frequency, which will alias into the baseband frequency range. And the ADC's digital sampling process introduces some quantization error (rounding error), which manifests as low-level noise. These errors can be kept within the requirements of the targeted application (e.g. under the limited dynamic range of human hearing for audio applications).

Sign in to keep reading

4 more chapters are free with a Lably account.

More in Computing and communication