Understanding and Optimizing Sampled Data Systems (Part I)
We take for granted that achieving the best results in our signal chain designs, requires a good understanding of interfacing with sensors, dealing with component noise, parasitics, thermal drift, etc., but sometimes we overlook the fact that the very act of data conversion from analog to digital (or from digital to analog) creates many errors in its own right. Quantization noise, phantom signals, artifacts, and distortion, are just some of the many conversion-related anomalies that must be considered. Filters, PCB grounding, and converter-support components such as clocks, voltage references, and power supplies, also directly impact performance.
In this two-part webinar series, we’ll take an in-depth look at data sampling and the many unique design issues that it creates, and more importantly, how to deal with them to optimize your design. You’ll gain a deeper understanding of quantization error and noise, aliasing, under-, and over-sampling, jitter, dither, slew and skew, and much more. Join us for Part I of this intensive and enlightening series.
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