Webinar recording — Improving the SNR of low-duty-cycle signals with a boxcar averager
Overview
In this webinar, we explore the fundamental principles of the boxcar averager and compare its applications to other averaging techniques. We also demonstrate its capabilities using Moku Cloud Compile, a versatile tool included on FPGA-based Moku devices that enables users to quickly deploy custom functions with no FPGA programming experience required.
What we covered:
- Learn how a boxcar averager with a static gate extracts key information from a noisy, low-duty-cycle signal, with a trigger signal and configurable system parameters.
- See the waveform recovery mode of the boxcar averager with the Moku Python API.
- Learn how to subtract DC baselines using a dual boxcar averager.
- Find out new ways to utilize the boxcar averager in conjunction with other FPGA-based Moku instruments to create custom signal processing pipelines in Multi-instrument Mode.
The webinar includes a presentation, demonstration, and live Q&A session.
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