Understanding and Optimizing Sampled Data Systems (Part II)
Data conversion from analog to digital (or from digital to analog) is an important element in many forms of electronic systems, but the technique of data sampling creates many design issues and considerations. Part I of this webinar series covered the fundamentals of data sampling and explored the effects of quantization, under- and oversampling, process gain, anti-alias filtering, and much more.
Part II will take a detailed look at the prevailing data converter architectures and provide an understanding of where sampling vs. quantization vs. digitization takes place, and more importantly, how this impacts the correct choice of converter for a given application. The sources and management of sampling anomalies effecting linearity, distortion, and noise will be discussed, along with many tried and true data converter application tips and techniques to insure an optimum system design.
Please disable any pop-up blockers for proper viewing of this webinar.