Shengli Xie mainly focuses on Smart grid, Computer network, Blind signal separation, Matrix decomposition and Algorithm. His work deals with themes such as Distributed algorithm, Distributed computing, Energy management, Energy consumption and Optimization problem, which intersect with Smart grid. The study of Computer network is intertwined with the study of Cognitive radio in a number of ways.
He interconnects Data mining, Multiset, Matrix, Sparse matrix and Component analysis in the investigation of issues within Blind signal separation. The study incorporates disciplines such as Generalization and Feature extraction in addition to Matrix decomposition. His study in Algorithm is interdisciplinary in nature, drawing from both Evolutionary computation, Probabilistic logic and Cluster analysis.
Shengli Xie mostly deals with Algorithm, Artificial intelligence, Cluster analysis, Blind signal separation and Matrix. His research in Algorithm is mostly focused on Sparse approximation. His Sparse approximation study combines topics from a wide range of disciplines, such as Underdetermined system and Sparse matrix.
Shengli Xie has researched Artificial intelligence in several fields, including Machine learning, Computer vision and Pattern recognition. The Cluster analysis study combines topics in areas such as Graph, Subspace topology, Non-negative matrix factorization and Graph. His work is dedicated to discovering how Blind signal separation, Matrix decomposition are connected with Computational complexity theory and other disciplines.
Shengli Xie focuses on Algorithm, Cluster analysis, Matrix, Artificial intelligence and Matrix decomposition. A large part of his Algorithm studies is devoted to Optimization problem. His Cluster analysis research includes elements of Graph, Feature, Representation, Sparse matrix and Graph.
His Matrix research integrates issues from Time domain, Structure, Blind signal separation, Independent component analysis and Frequency domain. His biological study spans a wide range of topics, including Machine learning and Pattern recognition. His research in Matrix decomposition is mostly concerned with Non-negative matrix factorization.
Shengli Xie spends much of his time researching Cluster analysis, Algorithm, Matrix, Matrix decomposition and Non-negative matrix factorization. His biological study deals with issues like Graph, which deal with fields such as Graph, Tucker decomposition, Rank and Spectral gap. His research in Algorithm intersects with topics in Representation, Sparse matrix, Unsupervised learning, Fourier transform and Frequency domain.
His studies in Matrix integrate themes in fields like Time domain, Optimization problem, Independent component analysis and Blind signal separation. His research investigates the connection with Matrix decomposition and areas like Computational complexity theory which intersect with concerns in Dimension, Trace, Embedding and Lemma. His work carried out in the field of Artificial intelligence brings together such families of science as Laplacian matrix and Rank.
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Home M2M networks: Architectures, standards, and QoS improvement
Yan Zhang;Rong Yu;Shengli Xie;Wenqing Yao.
IEEE Communications Magazine (2011)
Underdetermined blind source separation based on sparse representation
Yuanqing Li;S. Amari;A. Cichocki;D.W.C. Ho.
IEEE Transactions on Signal Processing (2006)
Cognitive machine-to-machine communications: visions and potentials for the smart grid
Yan Zhang;Rong Yu;Maziar Nekovee;Yi Liu.
IEEE Network (2012)
Gradient-Based Structural Similarity for Image Quality Assessment
Guan-Hao Chen;Chun-Ling Yang;Sheng-Li Xie.
international conference on image processing (2006)
Cognitive radio based hierarchical communications infrastructure for smart grid
Rong Yu;Yan Zhang;S. Gjessing;Chau Yuen.
IEEE Network (2011)
An ant colony optimization algorithm for image edge detection
Jing Tian;Weiyu Yu;Shengli Xie.
world congress on computational intelligence (2008)
Blockchain for Secure and Efficient Data Sharing in Vehicular Edge Computing and Networks
Jiawen Kang;Rong Yu;Xumin Huang;Maoqiang Wu.
IEEE Internet of Things Journal (2019)
Peak-to-Average Ratio Constrained Demand-Side Management With Consumer's Preference in Residential Smart Grid
Yi Liu;Chau Yuen;Shisheng Huang;Naveed Ul Hassan.
IEEE Journal of Selected Topics in Signal Processing (2014)
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
Derong Liu;Murad Abu-Khalaf;Adel M. Alimi;Charles Anderson.
Edge-Based Structural Similarity for Image Quality Assessment
Guan-Hao Chen;Chun-Ling Yang;Lai-Man Po;Sheng-Li Xie.
international conference on acoustics, speech, and signal processing (2006)
Profile was last updated on December 6th, 2021.
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