Publication

Optimal filtering of incremental first-order sigma-delta modulators with sweep input

Maher Kayal, François Krummenacher
2011
Conference Papers

Abstract

In this paper, an optimal filter design procedure is described, from the equation representing the behaviour of a ΣΔ modulator to a functional algorithm. The first section shows the design of an optimal filter for a first-order ΣΔ ADC with a constant input. Next, an algorithm for a time-varying input is detailed. The last algorithm allows an optimal decoding of high-resolution ADCs without an SH circuit.

Official source

https://infoscience.epfl.ch/entities/publication/b3b75d41-32c7-4b6b-8d8b-54617bba5320

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Maher Kayal, François Krummenacher
2011
Conference Papers

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/b3b75d41-32c7-4b6b-8d8b-54617bba5320

About this result

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For statistics and control theory, Kalman filtering, also known as linear quadratic estimation (LQE), is an algorithm that uses a series of measurements observed over time, including statistical noise and other inaccuracies, and produces estimates of unknown variables that tend to be more accurate than those based on a single measurement alone, by estimating a joint probability distribution over the variables for each timeframe. The filter is named after Rudolf E. Kálmán, who was one of the primary developers of its theory.

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Optimal filtering of incremental first-order sigma-delta modulators with sweep input

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