An analog-to-digital converter (ADC)'s dynamic range is critical during sampling analog
signals. A modulo operation prior to sampling can be used to enhance the effective dynamic …

Analog-to-digital converters (ADCs) facilitate the conversion of analog signals into a digital
format. While the specific designs and settings of ADCs can vary depending on their …

Common artefacts such as baseline drift, rescaling, and noise critically limit the performance
of machine learning-based automated ECG analysis and interpretation. This study proposes …

In this paper, we consider the problem of recovering a sum of filtered Diracs, representing an
input with finite rate of innovation (FRI), from its corresponding time encoding machine …

Analog-to-digital converters (ADCs) are key components of digital signal processing.
Classical samplers in this framework are controlled by a global clock. At high sampling rates …

We present a signal driven multi-channel time encoding system for sampling signals with
finite rate of innovation (FRI). The system produces samples in the form of finite differences …

Neuromorphic sampling is a paradigm shift in analog-to-digital conversion where the
acquisition strategy is opportunistic and measurements are recorded only when there is a …

Leaky integrate-and-fire (LIF) encoding is a model of neuron transfer function in biology that
has recently attracted the attention of the signal processing and neuromorphic computing …

This paper investigates the problem of sampling and reconstructing bandpass signals using
two-channel time encoding machine (TEM). It is shown that the sampling in principle is …

Neuromorphic sampling is a bioinspired and opportunistic analog-to-digital conversion
technique, where the measurements are recorded only when there is a significant change in …