.png){kind=icon}
返回
A New Modulation Recognition Method Based on Flying Fish Swarm Algorithm
.png){kind=icon}
OA
AI
DOI：10.1109/ACCESS.2021.3079131.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
The modulation recognition method based on deep learning plays a significant role in the intelligent communication system. To further improve the recognition rate, especially in the case of small samples with a low signal-to-noise ratio, this paper proposes a new modulation recognition method based on flying fish swarm algorithm. First, Short-Time Fourier Transform, Choi-Williams Distribution, and Cyclic Spectrum are combined to complete multi-channel signal processing. Second, AlexNet, VGGNet, GoogLeNet, and ResNet are transferred to realize feature extraction. Third, the support vector machine classifies the modulations after dimension reduction and feature fusion. Finally, the flying fish swarm is proposed to optimize the signal processing methods, the types of networks, the layers of networks, the dimensions of features, and the parameters of the support vector machine. The method can accurately recognize BPSK, QPSK, OQPSK, 8PSK, 4ASK, QAM16, QAM32, and QAM64. The simulation results show that the average recognition rate of modulation is 94.5% at SNR of 0 dB and 84.7% at SNR of -4 dB. Besides, the proposed modulation recognition method possesses good robustness under low SNR conditions.
Keyword:
Modulation
Signal processing algorithms
Feature extraction
Signal processing
Support vector machines
Signal to noise ratio
Transfer learning
Modulation recognition
deep learning
flying fish swarm algorithm
multi-channel signal processing
feature extraction
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
3.6
论文数:
9.8W
被引数:
29.4W
机构
引用论文
Extension of PCA to Higher Order Data Structures: An Introduction to Tensors, Tensor Decompositions, and Tensor PCA将PCA扩展到高阶数据结构: 张量，张量分解和张量PCA简介.png)
PROCEEDINGS OF THE IEEEOAAI
PROCEEDINGS OF THE IEEEIF25.9
OAAI分享收藏分享收藏Expression of ΔF508 Cystic Fibrosis Transmembrane Regulator (CFTR) Decreases Membrane Sialylation
OAAI
OAAI分享收藏Analysis of Network Coverage Optimization Based on Feedback K-Means Clustering and Artificial Fish Swarm Algorithm基于反馈k-means聚类和人工鱼群算法的网络覆盖优化分析IEEE ACCESSOAAI
IEEE ACCESSIF3.6
OAAI分享收藏
查看更多内容