28 citations · 44 across the 7 of their papers we have counts for
7 papers
Reassessing Layer Pruning in LLMs: New Insights and Methods
Yao Lu, Hao Cheng, Yujie Fang +6
Although large language models (LLMs) have achieved remarkable success across various domains, their considerable scale necessitates substantial computational resources, posing sig…
MDM: Advancing Multi-Domain Distribution Matching for Automatic Modulation Recognition Dataset Synthesis
Dongwei Xu, Jiajun Chen, Yao Lu +5
Recently, deep learning technology has been successfully introduced into Automatic Modulation Recognition (AMR) tasks. However, the success of deep learning is all attributed to th…
A Generic Layer Pruning Method for Signal Modulation Recognition Deep Learning Models
Yao Lu, Yutao Zhu, Yuqi Li +4
With the successful application of deep learning in communications systems, deep neural networks are becoming the preferred method for signal classification. Although these models…
Mixing Signals: Data Augmentation Approach for Deep Learning Based Modulation Recognition
Xinjie Xu, Zhuangzhi Chen, Dongwei Xu +5
With the rapid development of deep learning, automatic modulation recognition (AMR), as an important task in cognitive radio, has gradually transformed from traditional feature ext…
Deep Transfer Clustering of Radio Signals
Qi Xuan, Xiaohui Li, Zhuangzhi Chen +3
Modulation recognition is an important task in radio signal processing. Most of the current researches focus on supervised learning. However, in many real scenarios, it is difficul…
Adaptive Visibility Graph Neural Network and its Application in Modulation Classification
Qi Xuan, Kunfeng Qiu, Jinchao Zhou +4
Our digital world is full of time series and graphs which capture the various aspects of many complex systems. Traditionally, there are respective methods in processing these two d…
CLPVG: Circular limited penetrable visibility graph as a new network model for time series
Qi Xuan, Jinchao Zhou, Kunfeng Qiu +3
Visibility Graph (VG) transforms time series into graphs, facilitating signal processing by advanced graph data mining algorithms. In this paper, based on the classic Limited Penet…