Results 11 to 20 of about 15,987 (217)
Modeling and Control of Lip Based on Double-Layer Muscle
Journal of Algorithms & Computational Technology, 2014 Lip model plays an important role in virtual facial expression and speech simulation. However, the structures and movements of existing lip models are very simple, and the common motions such as protruding, pouting and sipping are failed to totally ...
Chen Zhi-Xiang +3 more
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Matroidal Structure of Generalized Rough Sets Based on Tolerance Relations
The Scientific World Journal, 2014 Rough set theory provides an effective tool to deal with uncertain, granular, and incomplete knowledge in information systems. Matroid theory generalizes the linear independence in vector spaces and has many applications in diverse fields, such as ...
Hui Li, Yanfang Liu, William Zhu
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Covering-Based Rough Sets on Eulerian Matroids
Journal of Applied Mathematics, 2013 Rough set theory is an efficient and essential tool for dealing with vagueness and granularity in information systems. Covering-based rough set theory is proposed as a significant generalization of classical rough sets.
Bin Yang, Ziqiong Lin, William Zhu
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IEEE Access, 2021 Granular computing is usually considered as a representative method for solving complex problems, which can be solved quickly through freely switching among different granular models.
Jinhui Li, Yunfeng Dong
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Cost-Sensitive Feature Selection of Numeric Data with Measurement Errors
Journal of Applied Mathematics, 2013 Feature selection is an essential process in data mining applications since it reduces a model’s complexity. However, feature selection with various types of costs is still a new research topic.
Hong Zhao, Fan Min, William Zhu
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Matroidal Structure of Rough Sets Based on Serial and Transitive Relations
Journal of Applied Mathematics, 2012 The theory of rough sets is concerned with the lower and upper approximations of objects through a binary relation on a universe. It has been applied to machine learning, knowledge discovery, and data mining. The theory of matroids is a generalization of
Yanfang Liu, William Zhu
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Supervised Learning via Unsupervised Sparse Autoencoder
IEEE Access, 2018 Dimensionality reduction is commonly used to preprocess high-dimensional data, which is an essential step in machine learning and data mining. An outstanding low-dimensional feature can improve the efficiency of subsequent learning tasks.
Jianran Liu, Chan Li, Wenyuan Yang
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Geometric Lattice Structure of Covering-Based Rough Sets through Matroids
Journal of Applied Mathematics, 2012 Covering-based rough set theory is a useful tool to deal with inexact, uncertain, or vague knowledge in information systems. Geometric lattice has been widely used in diverse fields, especially search algorithm design, which plays an important role in ...
Aiping Huang, William Zhu
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Distributed Decisions on TV Spectrum Allocation Considering Spatial and Temporal Variation
IEEE Access, 2018 TV spectrum has lower path loss, longer transmission range, and higher penetration capability, resulting in a wide range of potential important applications.
Zhenwei Chen +4 more
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Geometric Lattice Structure of Covering and Its Application to Attribute Reduction through Matroids
Journal of Applied Mathematics, 2014 The reduction of covering decision systems is an important problem in data mining, and covering-based rough sets serve as an efficient technique to process the problem.
Aiping Huang, William Zhu
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