Analog-to-Digital Compression: A new paradigm for converting signals to bits
Abstract
Processing, storing, and communicating information that originates as an analog signal involves converting this information to bits. This conversion can be described by the combined effect of sampling and quantization, as shown in Figure 1. The digital representation is achieved by first sampling the analog signal to represent it by a set of discrete-time samples and then quantizing these samples to a finite number of bits. Traditionally, these two operations are considered separately. The sampler is designed to minimize the information loss due to sampling based on characteristics of the continuous-time input. The quantizer is designed to represent the samples as accurately as possible, subject to a constraint on the number of bits that can be used in the representation. The goal of this article is to revisit this paradigm by illuminating the dependency between these two operations. In particular, we explore the requirements of the sampling system subject to the constraints on the available number of bits for storing, communicating, or processing the analog information.
- Publication:
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IEEE Signal Processing Magazine
- Pub Date:
- May 2018
- DOI:
- arXiv:
- arXiv:1801.06718
- Bibcode:
- 2018ISPM...35c..16K
- Keywords:
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- Computer Science - Information Theory;
- Computer Science - Systems and Control
- E-Print:
- to appear in "Signal Processing Magazine"