Lower Bounds on the Performance of Analog to Digital Converters
Mitra Osqui, Alexandre Megretski, Mardavij Roozbehani

TL;DR
This paper establishes certified lower bounds on ADC performance by modeling it as a dynamic game and solving a Bellman inequality, providing a systematic way to evaluate ADC efficiency.
Contribution
It introduces a novel dynamic game framework and numerical method to compute certified lower bounds for ADC performance, considering quantized disturbances.
Findings
Derived a Bellman-type inequality for ADC performance bounds.
Developed a numerical approach for computing the value function and worst-case input.
Proved properties of the value function that facilitate iterative computation.
Abstract
This paper deals with the task of finding certified lower bounds for the performance of Analog to Digital Converters (ADCs). A general ADC is modeled as a causal, discrete-time dynamical system with outputs taking values in a finite set. We define the performance of an ADC as the worst-case average intensity of the filtered input matching error, defined as the difference between the input and output of the ADC. The passband of the shaping filter used to filter the error signal determines the frequency region of interest for minimizing the error. The problem of finding a lower bound for the performance of an ADC is formulated as a dynamic game problem in which the input signal to the ADC plays against the output of the ADC. Furthermore, the performance measure must be optimized in the presence of quantized disturbances (output of the ADC) that can exceed the control variable (input of…
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Taxonomy
TopicsControl Systems and Identification · Advanced Control Systems Optimization · Stability and Control of Uncertain Systems
