An Interpretable Explanation Approach for Signal Modulation Classification
Signal modulation classification (SMC) has attracted extensive attention for its wide
application in the military and civil fields. The current direction of combining deep-learning …
application in the military and civil fields. The current direction of combining deep-learning …
Toward Learning Model-Agnostic Explanations for Deep Learning-Based Signal Modulation Classifiers
Y Tian, D Xu, E Tong, R Sun, K Chen… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
Recent advances in deep learning (DL) have brought tremendous gains in signal
modulation classification. However, DL-based classifiers lack transparency and …
modulation classification. However, DL-based classifiers lack transparency and …
Signal modulation classification based on deep belief network
W Li, Z Dou, C Wang, Y Zhang - 2019 IEEE Globecom …, 2019 - ieeexplore.ieee.org
Modulation classification plays an important role in civil and military fields such as software
defined radio, electronic countermeasure and intelligent demodulator. Due to the difficulty of …
defined radio, electronic countermeasure and intelligent demodulator. Due to the difficulty of …
Explainable neural network-based modulation classification via concept bottleneck models
LJ Wong, S McPherson - 2021 IEEE 11th Annual Computing …, 2021 - ieeexplore.ieee.org
While Radio Frequency Machine Learning (RFML) is expected to be a key enabler of future
wireless standards, a significant challenge to the widespread adoption of RFML techniques …
wireless standards, a significant challenge to the widespread adoption of RFML techniques …
Integrating Prior Knowledge and Contrast Feature for Signal Modulation Classification
With the advancement of Internet of Things technology, the need for sophisticated signal
modulation classification (SMC) has intensified, ensuring seamless communication and …
modulation classification (SMC) has intensified, ensuring seamless communication and …
Towards explainability for AI-based edge wireless signal automatic modulation classification
With the development of artificial intelligence technology and edge computing technology,
deep learning-based automatic modulation classification (AI-based AMC) deployed at edge …
deep learning-based automatic modulation classification (AI-based AMC) deployed at edge …
Complex-valued Depth-wise Separable Convolutional Neural Network for Automatic Modulation Classification
C Xiao, S Yang, Z Feng - IEEE Transactions on Instrumentation …, 2023 - ieeexplore.ieee.org
Automatic modulation classification (AMC) is a critical task in industrial cognitive
communication systems. Existing state-of-the-art methods, typified by real-valued …
communication systems. Existing state-of-the-art methods, typified by real-valued …
Towards next-generation signal intelligence: A hybrid knowledge and data-driven deep learning framework for radio signal classification
S Zheng, X Zhou, L Zhang, P Qi, K Qiu… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
Automatic modulation classification (AMC) can generally be divided into knowledge-based
methods and data-driven methods. In this paper, we explore combining the knowledge …
methods and data-driven methods. In this paper, we explore combining the knowledge …
A hierarchical classification head based convolutional gated deep neural network for automatic modulation classification
Automatic modulation classification (AMC) identifies a received signal's modulation scheme
without prior knowledge of the intercepted signal, which enables significant applications in …
without prior knowledge of the intercepted signal, which enables significant applications in …
Feature explainable deep classification for signal modulation recognition
Signal modulation recognition plays a critical role in many fields to identify the modulation
type of wireless signals. Since the deep learning based models have achieved great …
type of wireless signals. Since the deep learning based models have achieved great …