[HTML][HTML] Deep learning-based fault location framework in power distribution grids employing convolutional neural network based on capsule network

H Mirshekali, A Keshavarz, R Dashti, S Hafezi… - Electric Power Systems …, 2023 - Elsevier
Power distribution grids (PDGs) are one of the main parts of electrical logistic chains with the
task of transferring electricity to the consumers continually. Adverse weather conditions …

Automatic modulation classification of radar signals using the Rihaczek distribution and Hough transform

D Zeng, X Zeng, H Cheng, B Tang - IET Radar, Sonar & Navigation, 2012 - IET
It is an important work to classify the modulation type of the intercepted radar signal for an
electronic intelligence (ELINT) receiver in a non-cooperative environment. The authors use …

Intra-pulse modulation recognition using short-time ramanujan Fourier transform spectrogram

X Ma, D Liu, Y Shan - EURASIP journal on advances in signal processing, 2017 - Springer
Intra-pulse modulation recognition under negative signal-to-noise ratio (SNR) environment
is a research challenge. This article presents a robust algorithm for the recognition of 5 types …

An efficient FPGA IP core for automatic modulation classification

C Cardoso, AR Castro, A Klautau - IEEE Embedded Systems …, 2013 - ieeexplore.ieee.org
This letter presents a new algorithm for automatic modulation classification (AMC) and its
implementation and validation as an intellectual property (IP) core. AMC aims at accurately …

Signal area estimation based on deep learning

MM Alammar, M López-Benítez - Physical Communication, 2023 - Elsevier
In many practical application scenarios, radio communication signals are commonly
represented as a spectrogram, which represents the signal strength measured at multiple …

Accurate Automatic Extraction of Signal Components From Noisy Radio Spectrograms

M López-Benítez, MM Alammar - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
In some radio communication scenarios it is useful to extract the bandwidth and start/end
times of each transmission in a spectrogram. However, few methods in the literature are able …

Signal analysis and classification of digital communication signals using adaptive smooth-windowed Wigner-Ville distribution

JL Tan, AZ bin Sha'ameri - 2008 6th National Conference on …, 2008 - ieeexplore.ieee.org
Signals in a non cooperative communication environment such as in the high frequency
(HF) spectrum are generally unknown in nature. There is a need for true spectrum …

Data Mining Applied to cognitive radio systems

L Freitas, Y Pires, J Morais, J Costa, A Klautau - 2012 - books.google.com
Cognitive radio (CR) is a novel technology that allows to improve spectrum utilization by
enabling opportunistic access to the licensed spectrum band by unlicensed users [2]. This is …

Iterative Pyramidal Filtering Method for Improved Signal Recognition in Radio Spectrograms

M López-Benítez - IEEE Wireless Communications Letters, 2022 - ieeexplore.ieee.org
Spectrograms are an essential time-frequency representation tool that has been used to
address several important problems in wireless communication systems. However, most …

Use of the cross time-frequency distribution for the analysis of the class of PSK signals

CY Mei, AZ Sha'ameri - International Conference on Computer …, 2010 - ieeexplore.ieee.org
Phase Shift-Keying (PSK) modulation has been applied widely in most of the data
communication system nowadays due to its noise immunity and bandwidth efficiency …