Results 31 to 40 of about 3,104,277 (280)

Training Images Generation for CNN Based Automatic Modulation Classification

IEEE Access, 2021
Convolutional neural network (CNN) models have recently demonstrated impressive classification and recognition performance on image and video processing scope.
Wei-Tao Zhang, Dan Cui, Shun-Tian Lou
doaj   +1 more source

Automatic Digital Modulation Classification Based on Curriculum Learning

Applied Sciences, 2019
Neural network shows great potential in modulation classification because of its excellent accuracy and achievability but overfitting and memorizing data noise often happen in previous researches on automatic digital modulation classifier.
Min Zhang, Zhongwei Yu, Hai Wang, Hongbo Qin, Wei Zhao, Yan Liu   +5 more
doaj   +1 more source

A knowledge distillation strategy for enhancing the adversarial robustness of lightweight automatic modulation classification models

IET Communications
Automatic modulation classification models based on deep learning models are at risk of being interfered by adversarial attacks. In an adversarial attack, the attacker causes the classification model to misclassify the received signal by adding carefully
Fanghao Xu, Chao Wang, Jiakai Liang, Chenyang Zuo, Keqiang Yue, Wenjun Li   +5 more
doaj   +1 more source

Automatic Modulation Classification Using Compressive Convolutional Neural Network

IEEE Access, 2019
The deep convolutional neural network has strong representative ability, which can learn latent information repeatedly from signal samples and improve the accuracy of automatic modulation classification (AMC).
Sai Huang, Lu Chai, Zening Li, Di Zhang, Yuanyuan Yao, Yifan Zhang, Zhiyong Feng   +6 more
doaj   +1 more source

Automatic modulation classification of digital modulations in presence of HF noise [PDF]

EURASIP Journal on Advances in Signal Processing, 2012
Designing an automatic modulation classifier (AMC) for high frequency (HF) band is a research challenge. This is due to the recent observation that noise distribution in HF band is changing over time. Existing AMCs are often designed for one type of noise distribution, e.g., additive white Gaussian noise.
Alharbi Hazza, Mobien Shoaib, Saleh A. Alshebeili, Fahd A. Alturki   +3 more
openaire   +1 more source

PAK1 activation drives divergent resistance mechanisms to aromatase inhibition and tamoxifen in a luminal: A breast cancer model

Molecular Oncology, EarlyView.
Breast cancer remains a major cause of cancer death in women, frequently developing endocrine therapy resistance. This study demonstrates that upregulated p21‐activated kinase 1 (PAK1) activity drives resistance to tamoxifen and long‐term estrogen deprivation in ER+ breast cancer models.
Luisa Schwarzmüller, Janina Müller, Efstathios‐Iason Vlachavas, Lukas Beumers, Lena Fleischhacker, Sara Burmester, Angelika Wörner, Sabine Karolus, Dominic Helm, Cindy Körner, Stefan Wiemann   +10 more
wiley   +1 more source

Automatic modulation classification via instantaneous features

, 2015
Automatic modulation classification has attracted a lot of interests in the research community in recent years due to the advances in cognitive RF signal processing such as cognitive radio, cognitive radar and cognitive electronic warfare.
Moran, Michael K., Wu, Zhiqiang, Zhiqiang Wu, Li, Dong, Dong Li, Elliott Moser, Erric Hillen, Michael K. Moran, Moser, Elliott, Hillen, Erric   +9 more
core   +1 more source

Automatic modulation classification based deep learning with mixed feature [PDF]

, 2023
The automatic modulation classification (AMC) plays an important and necessary role in the truncated wireless signal, which is used in modern communications.
Shah, Ali H., Tariq M. Salman, Miry, Abbas Hussien, Abbas Hussien Miry, Salman, Tariq M., Ali H. Shah   +5 more
core   +1 more source

In vitro and in silico modelling of ROS1‐positive non‐small cell lung cancer reveals fusion‐dependent tyrosine kinase inhibitor responses

Molecular Oncology, EarlyView.
Drug resistance limits treatment success in a subset of lung cancers driven by ROS1 gene alterations. Using patient‐derived cells and computer simulations, we studied three key mutations and how they affect five targeted drugs. The mutations reduced drug effectiveness in different ways by altering protein structure and behavior.
Farhan Ul Haq, Marc Terrones, Felicia Rodrigues Fortes, Anne Schepers, Alessia Denis, Christophe Deben, Ken Op de Beeck, Guy Van Camp, Geert Vandeweyer   +8 more
wiley   +1 more source

CSA-Assisted Gabor Features for Automatic Modulation Classification

, 2021
Automatic modulation classification (AMC) is a process of automatic detection of modulation format imposed on the received signal with no prior information (carrier, signal power, phase offset) of the signal, also known as blind classification.
Shah Syed Ihtesham Hussain, Ghauri Sajjad A, Sarfraz Mubashar, Coronato Antonio, Alam Sheraz   +4 more
core   +1 more source