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The remarkable ability of deep learning (DL) models to approximate high-dimensional functions from samples has sparked a revolution across numerous scientific and industrial domains that cannot be overemphasized. In sensitive applications, the good perform ...
We present a statistical framework to benchmark the performance of reconstruction algorithms for linear inverse problems, in particular, neural-network-based methods that require large quantities of training data. We generate synthetic signals as realizati ...
Shannon's sampling theorem for bandlimited signals, formulated in 1949, has become a cornerstone for modern digital communications and signal processing. The importance of sampling and reconstruction of analog signals has led to great advances in the field ...
Remote photoplethysmography (rPPG) using camera-based imaging has shown excellent potential recently in vital signs monitoring due to its contactless nature. However, the optimum filter selection for pre-processing rPPG data in signal conditioning is still ...
Sentiment analysis is the automated coding of emotions expressed in text. Sentiment analysis and other types of analyses focusing on the automatic coding of textual documents are increasingly popular in psychology and computer science. However, the potenti ...
Purpose: To develop a scan-specific model that estimates and corrects k-space errors made when reconstructing accelerated MRI data. Methods: Scan-specific artifact reduction in k-space (SPARK) trains a convolutional-neural-network to estimate and correct k ...
In the analysis of power grid waveforms, the presence of amplitude or phase steps can disrupt the estimation of frequency and rate-of-change-of-frequency (ROCOF). Standard methods based on phasor-models fail in the extraction of signal parameters during th ...
Data imputation of incomplete image sequences is an essential prerequisite for analyzing and monitoring all development stages of plants in precision agriculture. For this purpose, we propose a conditional Wasserstein generative adversarial network TransGr ...
Power-Hardware-In-the-Loop (PHIL) setups have gained high importance in validation of the performance of newly developed algorithms and devices with low risk and implementation cost. However, the interconnection of a power hardware with a simulated model v ...
This article presents a two-times interleaved, loop-unrolled SAR analog-to-digital converter (ADC) operational from 300 down to 4.2 K. The 6-8-bit resolution and the sampling speed up to 1 GS/s are targeted at digitizing the multi-channel frequency-multipl ...
