Introduction into Programmable Arbitrary Waveform Generators and General Signal Generation
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Signal generation is a cornerstone of electronics testing, research, and system validation. It enables engineers to
create precise electrical stimuli that mimic real-world conditions, verify device behavior, or simulate sensor outputs
and communication signals.

Traditional function generators are limited to a small set of predefined periodic waveforms (sine, square, triangle,
ramp, pulse) with adjustable frequency, amplitude, offset, and duty cycle. They serve well for basic tasks but lack
the flexibility to reproduce complex, irregular, or application-specific signals.

Programmable Arbitrary Waveform Generators (AWGs) overcome these limitations. An AWG stores a user-defined sequence of
digital sample points (voltage values at discrete time steps) in high-speed memory. These samples are clocked out at a
programmable sample rate and converted to a continuous analog signal by a high-resolution Digital-to-Analog Converter
(DAC).

The result: virtually any waveform shape can be generated—repetitive or single-shot, with glitches, noise, modulated
carriers, custom pulses, or even streamed real-time data.


Why It Matters for Testing
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AWGs are indispensable in communications testing, radar/sonar simulation, biomedical signal emulation, automotive ECU
validation, quantum control, and education. Their programmability makes them perfect for hardware-in-the-loop and
automated test environments.

This BalderHub package provides reusable scenarios, fixtures, and features for the Balder test framework, allowing you
to integrate programmable AWGs seamlessly into your Python-based test suites. You can now stimulate devices under
test with arbitrary signals, verify responses, and run fully automated, repeatable experiments - without reinventing
waveform control for every project.
