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Kangle Li

dblp:138/5881 · DBLP profile ↗
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4ranked-venue papers
0as first author
2since 2021 · last 2024
0000-0001-8778-3631ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1 · 1 since 2021Systems, architecture and hardware · 1 · 1 since 2021Graphics, computer vision, multimedia, augmented reality and games · 1Applied, interdisciplinary, general and emerging computing · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer networks
1 paper
Physical-layer communications · 100%

Topics — the 1 heaviest of 1, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Physical-layer communications › signal processing for communications
signal parameter estimation
0.212013
A new method of micro-motion parameters estimation based on cyclic autocorrelation function · Sci. China Inf. Sci. 2013

Methods — techniques the papers use, named apart from their topics

cyclic autocorrelation function · 0.2
YearPublicationVenuePosition
2024 RMSRM: real-time monitoring-based self-reconfiguration mechanism in reconfigurable PE array
Rui Shan, Kangle Li
J. Supercomput.4
2023 Hierarchical belief rule-based model for imbalanced multi-classification
Guanxiang Hu, Wei He 0008, Hailong Zhu, Kangle Li
Expert Syst. Appl.5
2015 Parameter Estimation of Radar Targets with Macro-Motion and Micro-Motion Based on Circular Correlation Coefficients
abstract
Micro-Doppler (m-D) signatures induced by micro-motion dynamics, which are of great importance for target classification, have received increasing attention among the radar community. For scenarios when the micro-motion of radar target is accompanied by macro-motion, the periodicity of m-D is disturbed by macro-motion. In that case, extraction of micro-motion signatures based on the periodicity of time-frequency representation (TFR) of the radar echo may become invalid. In this work, we show that the periodicity of TFR is replaced by circular periodicity in the presence of macro-motion. In view of this, the circular correlation coefficients of TFR are employed to characterize the circular periodicity of TFR and to provide an estimate of the micro-motion period. The property of circular correlation coefficients enables us to estimate the micro-motion period of radar targets in the presence of macro-motion. Experiments with synthetic data and measured radar data validate the effectiveness of the proposed method.
Wenpeng Zhang 0002, Kangle Li, Weidong Jiang
IEEE Signal Process. Lett.2
2013 A new method of micro-motion parameters estimation based on cyclic autocorrelation function
Jie Niu, Kangle Li, Weidong Jiang, Xiang Li 0014, Gangyao Kuang
Sci. China Inf. Sci.2