TrackⅣ

Signal Analysis, Feature Extraction and Intelligent Recognition(Submission Deadline: October 31, 2026) 信号分析、特征提取与智能识别

Chair:

Yuxing Li
Xi’an University of Technology, China

Topics:
Theories and Methods for Signal Analysis (信号分析理论与方法) Time-Frequency Analysis (时频分析) Signal Decomposition (信号分解) Signal Denoising, Enhancement, and Reconstruction (信号去噪、增强与重构) Nonlinear Analysis and Complexity Measures (非线性分析与复杂度度量) Feature Extraction, Selection, and Fusion (特征提取、选择与融合) Multisource, Multichannel, and Multimodal Signal Processing (多源、多通道与多模态信号处理) Machine Learning and Deep Learning for Signal Processing (面向信号处理的机器学习与深度学习) Pattern Recognition and Intelligent Classification (模式识别与智能分类) Condition Monitoring, Anomaly Detection, and Intelligent Sensing Applications (状态监测、异常检测与智能感知应用)

Summary:
Multisource, nonstationary, and noise-contaminated signals are widely encountered in complex engineering systems and environmental sensing applications. Effective signal analysis, feature extraction, and intelligent recognition of such signals are of great importance. This special session welcomes new methods and application-oriented studies in signal processing, machine learning, and related fields, including time-frequency analysis, complexity measures, feature extraction and fusion, deep learning, and intelligent classification. It aims to promote the application of advanced signal processing techniques in complex engineering systems and intelligent sensing scenarios.

复杂工程系统与环境感知中广泛存在多源、非平稳和含噪信号。对这些信号进行有效分析、特征提取与智能识别具有重要意义。本专题面向信号处理、机器学习及相关应用领域，征集信号时频分析、复杂度度量、特征提取与融合、深度学习及智能分类等方面的新方法与应用研究，推动先进信号处理技术在复杂工程系统与智能感知场景中的应用。