

Understanding sigma delta ADCs: A nonmathematical approachMohit Khajuria, Prashant Goyal and L Gupta, Freescale In this paper, we will attempt to explain sigma delta converters with a nonmathematical approach, covering the basic concepts of noise shaping and oversampling, explained with the help of some examples. These concepts along with digital decimation filters are later incorporated together to reveal the magic behind sigma delta converters. This paper also covers the basics of first and second order sigma delta ADCs and how the order of the sigma delta modulator impacts the performance of the ADC. Introduction Nowadays, there are many applications that often require analog to digital converters with high resolution but not with high accuracy and that calls for sigma delta ADC’s. To understand sigma delta converters, one has to dive into control loop theory with complex mathematics involved in the frequency domain. But this article will try to make you understand very important concepts like noise shaping, oversampling and the whole magic behind sigma delta modulators that differentiates them from the rest of the converter architectures, avoiding as much mathematical complexities as we can to give you a feel of visualizing things moving. In order to understand sigma delta ADCs, it is imperative to first understand the basic concepts of noise shaping and oversampling. Noise shaping is explained by using two analogies.

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