A5101649440- Fault Detection and Control Systems
- Advanced Battery Materials and Technologies
- Advancements in Battery Materials
- Advanced Control Systems Optimization
- Artificial Immune Systems Applications
- Metaheuristic Optimization Algorithms Research
- Fuel Cells and Related Materials
- Iterative Learning Control Systems
- Advancements in Solid Oxide Fuel Cells
- Stability and Control of Uncertain Systems
- Machine Fault Diagnosis Techniques
- Inorganic Chemistry and Materials
- Industrial Technology and Control Systems
- Advanced Battery Technologies Research
- Evolutionary Algorithms and Applications
- Caching and Content Delivery
- Neural Networks Stability and Synchronization
- Engineering Diagnostics and Reliability
- Opportunistic and Delay-Tolerant Networks
- Advanced Algorithms and Applications
- Machine Learning and ELM
- Advanced Computing and Algorithms
- Satellite Communication Systems
- vaccines and immunoinformatics approaches
- Gear and Bearing Dynamics Analysis
Xidian University
2008-2024
Huazhong University of Science and Technology
1994-2024
Zhejiang University of Technology
2012-2023
Harbin University of Science and Technology
2023
China University of Geosciences
2008-2021
Wuhan University of Technology
2016
University of Science and Technology of China
2008-2009
Guangdong University of Technology
2008
South China University of Technology
2008
This paper investigates the problem of delay-dependent robust <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">H</i> <sub xmlns:xlink="http://www.w3.org/1999/xlink">infin</sub> filtering design for a class uncertain discrete-time state-delayed Takagi-Sugeno (T-S) fuzzy systems. The state delay is assumed to be time-varying and an interval-like type, which means that both lower upper bounds are available. parameter uncertainties have structured...
This brief revisits the problem of delay-dependent robust H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">infin</sub> filtering design for discrete-time polytopic linear systems with interval-like time-varying delay. Under condition whether unknown parameters can be measured online or not, a parameter-dependent parameter-independent filter is respectively developed which guarantees asymptotic stability resulting error system performance gamma....
The loading amount of the cathode mixture has a significant impact on energy density all-solid-state lithium batteries (ASSLBs). Moreover, chemical/electrochemical instability argyrodite electrolytes toward bare layered materials also affects battery performances. However, effects electrode loading, which consists active and carbon additives, are not fully investigated. In this work, electrochemical performances Li6PS5Cl-based ASSLBs using LiNi0.7Mn0.2CO0.1O2 (NCM712) as with different...
This paper proposes a joint class metric and sparse representation regularized deep belief network (J-DBN) method for intelligent fault diagnosis of the rotary equipment. In this novel method, DBN is considered as pretraining to extract data features. It combines advantages both representation, which can optimize distance features in same penalize different classes, generate Specifically, new matrix constructed avoid using structural parameters local structure each sample. The J-DBN-based...
Fast and efficient disparity estimation compensation are the key techniques in multi-view video processing. When implementing coding, there lots of temporal inter-viewpoint redundancy among viewpoints, which makes compression work more challenging. It is found that relationship subject to epipolar geometry, provides constraints between two image sequences video. To efficiently encode data-intensive imaging content, a fast (DE) search method proposed this paper based on rectified lines....
In this paper, we introduce Lamarckian learning theory into the Clonal Selection Algorithm and propose a sort of Algorithm, termed as LCSA. The major aim is to utilize effectively information each individual reinforce exploitation with help local search. Recombination operator tournament selection are incorporated LCSA further enhance ability global exploration. We compare in solving twenty benchmark problems evaluate performance results demonstrate that search makes more effective efficient...
In this paper, we introduce Lamarckian learning theory into the clonal selection algorithm and propose a sort of algorithm, termed as LCSA. The major aim is to utilize effectively information each individual reinforce exploitation with help local search. Recombination operator tournament are incorporated LCSA further enhance ability global exploration. We compared (CSA) in solving twenty benchmark problems test performance results demonstrate that effective efficient numerical optimization problems.