Consider the recovery of an unknown signal x from quantized linear measurements. In the
one-bit compressive sensing setting, one typically assumes that x is sparse, and that the …

Recent results in one-bit sampling provide a framework for a relatively low-cost, low-power
sampling, at a high rate by employing time-varying sampling threshold sequences. Another …

One-bit quantization with time-varying sampling thresholds (also known as random
dithering) has recently found significant utilization potential in statistical signal processing …

Quantization is an essential step in digitizing signals, and, therefore, an indispensable
component of any modern acquisition system. This chapter explores the interaction of …

Noise sha** refers to an analog-to-digital conversion methodology in which quantization
error is arranged to lie mostly outside the signal spectrum by means of oversampling and …

The field of quantized compressed sensing investigates how to jointly design a
measurement matrix, quantizer, and reconstruction algorithm in order to accurately …

Modulo sampling and dithered one-bit quantization frame-works have emerged as
promising solutions to overcome the limitations of traditional analog-to-digital converters …

Conventional analog-to-digital converters (ADCs) are limited in dynamic range. If a signal
exceeds some prefixed threshold, the ADC saturates and the resulting signal is clipped, thus …

In this paper we study the quantization stage that is implicit in any compressed sensing
signal acquisition paradigm. We propose using Sigma–Delta (ΣΔ) quantization and a …

Suppose that the collection forms a frame for ℝ k, where each entry of the vector ei is a sub-
Gaussian random variable. We consider expansions in such a frame, which are then …