Sequence Data Representation Learning and Applications
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Computer Science & Engineering".
Deadline for manuscript submissions: 15 July 2025 | Viewed by 910
Special Issue Editors
Interests: deep learning; sequence data mining; pattern recognition
Interests: control theory and control engineering; navigation, guidance, and control; detection technology; automation devices
Interests: weak signal detection; nonlinear signal processing; vector DOA estimation
Special Issue Information
Dear Colleagues,
Data mining is a decision support process, which is mainly based on machine learning, pattern recognition, statistics, database, visualization technology, etc., to analyze data in practical applications in a high degree of automation, dig out potential patterns, or make inductive reasoning, and then assist decision-making. As an important branch of data mining, sequential data mining has important characteristics that are different from traditional data mining, which concerns how to find the evolution law of sequence data (e.g., electromagnetic information processing, radar navigation and positioning, communication, video, i.e., image sequence processing, robot perception, and energy fields, etc.). Sequence data mining is the right-hand man of informatization environment perception, understanding, data information, and the data into decision-making advantages. Sequence data representation and recognition. Considering the extensive and urgent requirement of this task, effective mining of relevant, useful information contained in data at any time or in the evolution of specific rules through sequence data modeling can effectively promote the development of sequence data mining, which has important theoretical significance for signal analysis and application. At the same time, it has important guiding significance for military and civilian fields.
This Special Issue aims to bring together cutting-edge research that explores the latest techniques and methodologies in sequence data mining, emphasizing their relevance and impact across diverse domains. By bridging the gaps between signal processing, video analysis, robot perception, and energy management, we endeavor to solve the common sequence data mining technologies in various military and civilian fields and verify these theory methods in the various military and civilian fields. Suggested themes for contributions include advanced algorithms for sequence pattern recognition, including signal processing, video analysis, energy safety,, etc. We invite researchers, practitioners, and industry experts to share their groundbreaking work and insights, contributing to the advancement of sequence data mining research and its real-world applications. Join us in this endeavor to shape the future of data-driven decision-making and optimization.
In this Special Issue, original research articles and reviews are welcome. Research areas may include (but not limited to) the following:
Theory:
- Sequence Data Mining;
- Deep Learning;
- Knowledge Graph;
- Signal Processing;
- ……
Applications:
- Video Analysis;
- Signal Recognition;
- Radar Target Detection;
- Electromagnetic Information Processing;
- Automatic Modulation Recognition;
- Specific Emitter Identification;
- Interference Suppression;
- Weak Signal Detection;
- Nonlinear Signal Processing;
- Vector DOA Estimation;
- Navigation and Positioning;
- Power Systems and Power Electronics;
- Robot Perception.
- ……
We look forward to receiving your contributions.
Dr. Zhigang Zhu
Prof. Dr. Yongfeng Zhi
Dr. Haitao Dong
Dr. Wenbo Zhang
Guest Editors
Manuscript Submission Information
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Keywords
- sequence data representation
- sequence data mining and applications
- pattern recognition
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