Learning-based compressive subsampling
The problem of recovering a structured signal x∈ C p from a set of dimensionality-reduced
linear measurements b= Ax arises in a variety of applications, such as medical imaging …
linear measurements b= Ax arises in a variety of applications, such as medical imaging …
Close encounters of the binary kind: Signal reconstruction guarantees for compressive Hadamard sampling with Haar wavelet basis
A Moshtaghpour, JM Bioucas-Dias… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
We investigate the problems of 1-D and 2-D signal recovery from subsampled Hadamard
measurements using Haar wavelet as a sparsity inducing prior. These problems are of …
measurements using Haar wavelet as a sparsity inducing prior. These problems are of …
Adaptive learning-based compressive sampling for low-power wireless implants
Implantable systems are nowadays being used to interface the human brain with external
devices, in order to understand and potentially treat neurological disorders. The most …
devices, in order to understand and potentially treat neurological disorders. The most …
Anomaly detection in invasively recorded neuronal signals using deep neural network: effect of sampling frequency
Abnormality detection has advanced in recent years with the help of machine learning, in
particular with deep learning models, which can predict accurately across many types of …
particular with deep learning models, which can predict accurately across many types of …
Learning-based near-optimal area-power trade-offs in hardware design for neural signal acquisition
Wireless implantable devices capable of monitoring the electrical activity of the brain are
becoming an important tool for understanding and potentially treating mental diseases such …
becoming an important tool for understanding and potentially treating mental diseases such …
Real-time dct learning-based reconstruction of neural signals
Wearable and implantable body sensor network systems are one of the key technologies for
continuous monitoring of patient's vital health status such as temperature and blood …
continuous monitoring of patient's vital health status such as temperature and blood …
Dct learning-based hardware design for neural signal acquisition systems
This work presents an area and power efficient encoding system for wireless implantable
devices capable of monitoring the electrical activity of the brain. Such devices are becoming …
devices capable of monitoring the electrical activity of the brain. Such devices are becoming …
[PDF][PDF] Computational interferometry for hyperspectral imaging
A Moshtaghpour - 2019 - dial.uclouvain.be
The idea of capturing hundreds to thousands images of an object, eg, biological specimen,
in different wavelengths has attracted decades of research under the name of HyperSpectral …
in different wavelengths has attracted decades of research under the name of HyperSpectral …
[PDF][PDF] Circuit and System Design for Low-Power and Minimally-Invasive Brain Implants
M Shoaran - cnl.ece.cornell.edu
Chronic neurological disorders cause enormous emotional and economic burdens on
society. Despite the progress in the field, many of these disorders remain undertreated …
society. Despite the progress in the field, many of these disorders remain undertreated …
Learning-Based Hardware Design for Data Acquisition Systems
C Aprile - 2018 - infoscience.epfl.ch
This multidisciplinary research work aims to investigate the optimized information extraction
from signals or data volumes and to develop tailored hardware implementations that trade …
from signals or data volumes and to develop tailored hardware implementations that trade …