Abstract
The paper deals with the task of optimal design 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, and its performance is defined as the worst-case average intensity of the filtered input matching error. The design task can be viewed as that of optimal quantized decision making in a system, with the objective being to optimize the performance measure. An algorithm is proposed for designing optimal ADCs and certifying their optimality. The algorithm is based on exploiting a special structure in the underlying dynamic program, which makes it possible to find the optimal value function, and hence the optimal quantization law exactly and analytically. Moreover, the designed ADC is shown to have the classical Delta-Sigma Modulator (DSM) structure with optimal quantization step spacing.
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