1 research outputs found
Time Encoding via Unlimited Sampling: Theory, Algorithms and Hardware Validation
An alternative to conventional uniform sampling is that of time encoding,
which converts continuous-time signals into streams of trigger times. This
gives rise to Event-Driven Sampling (EDS) models. The data-driven nature of EDS
acquisition is advantageous in terms of power consumption and time resolution
and is inspired by the information representation in biological nervous
systems. If an analog signal is outside a predefined dynamic range, then EDS
generates a low density of trigger times, which in turn leads to recovery
distortion due to aliasing. In this paper, inspired by the Unlimited Sensing
Framework (USF), we propose a new EDS architecture that incorporates a modulo
nonlinearity prior to acquisition that we refer to as the modulo EDS or MEDS.
In MEDS, the modulo nonlinearity folds high dynamic range inputs into low
dynamic range amplitudes, thus avoiding recovery distortion. In particular, we
consider the asynchronous sigma-delta modulator (ASDM), previously used for low
power analog-to-digital conversion. This novel MEDS based acquisition is
enabled by a recent generalization of the modulo nonlinearity called
modulo-hysteresis. We design a mathematically guaranteed recovery algorithm for
bandlimited inputs based on a sampling rate criterion and provide
reconstruction error bounds. We go beyond numerical experiments and also
provide a first hardware validation of our approach, thus bridging the gap
between theory and practice, while corroborating the conceptual underpinnings
of our work.Comment: 27 pgs, 11 figures, IEEE Trans. Sig. Proc., accepted with minor
revision