A deep cascade of convolutional neural networks for dynamic MR image reconstruction
Inspired by recent advances in deep learning, we propose a framework for reconstructing
dynamic sequences of 2-D cardiac magnetic resonance (MR) images from undersampled …
dynamic sequences of 2-D cardiac magnetic resonance (MR) images from undersampled …
A deep cascade of convolutional neural networks for MR image reconstruction
Abstract The acquisition of Magnetic Resonance Imaging (MRI) is inherently slow. Inspired
by recent advances in deep learning, we propose a framework for reconstructing MR images …
by recent advances in deep learning, we propose a framework for reconstructing MR images …
Complex-valued vs. real-valued neural networks for classification perspectives: An example on non-circular data
JA Barrachina, C Ren, C Morisseau… - ICASSP 2021-2021 …, 2021 - ieeexplore.ieee.org
This paper shows the benefits of using Complex-Valued Neural Network (CVNN) on
classification tasks for non-circular complex-valued datasets. Motivated by radar and …
classification tasks for non-circular complex-valued datasets. Motivated by radar and …
Theory and implementation of complex-valued neural networks
JA Barrachina, C Ren, G Vieillard, C Morisseau… - arXiv preprint arXiv …, 2023 - arxiv.org
This work explains in detail the theory behind Complex-Valued Neural Network (CVNN),
including Wirtinger calculus, complex backpropagation, and basic modules such as complex …
including Wirtinger calculus, complex backpropagation, and basic modules such as complex …
An input weights dependent complex-valued learning algorithm based on wirtinger calculus
Complex-valued neural network is a kind of learning model which can deal with problems in
complex domain. Fully complex extreme learning machine (CELM) is a much faster training …
complex domain. Fully complex extreme learning machine (CELM) is a much faster training …
Fully complex deep learning classifiers for signal modulation recognition in non-cooperative environment
S Kim, HY Yang, D Kim - IEEE Access, 2022 - ieeexplore.ieee.org
Deep learning (DL) classifiers have significantly outperformed traditional likelihood-based or
feature-based classifiers for signal modulation recognition in non-cooperative environments …
feature-based classifiers for signal modulation recognition in non-cooperative environments …
Imreconet: Learn to detect in index modulation aided mimo systems with complex valued neural networks
C Zhang, H Lu, J Liu - IEEE Transactions on Vehicular …, 2022 - ieeexplore.ieee.org
Index modulation (IM) reduces the power consumption and hardware cost of the multiple-
input multiple-output (MIMO) system by activating part of the antennas for data transmission …
input multiple-output (MIMO) system by activating part of the antennas for data transmission …
Learning representations using complex-valued nets
Complex-valued neural networks (CVNNs) are an emerging field of research in neural
networks due to their potential representational properties for audio, image, and …
networks due to their potential representational properties for audio, image, and …
The field of values of a matrix and neural networks
GM Georgiou - IEEE Transactions on Neural Networks and …, 2014 - ieeexplore.ieee.org
The field of values of a matrix, also known as the numerical range, is introduced in the
context of neural networks. Using neural network techniques, an algorithm and a …
context of neural networks. Using neural network techniques, an algorithm and a …