A5100691181- Advanced Control Systems Optimization
- Fault Detection and Control Systems
- Neural Networks Stability and Synchronization
- Advanced Algorithms and Applications
- Fuzzy Logic and Control Systems
- Control Systems and Identification
- Distributed Control Multi-Agent Systems
- Advanced Memory and Neural Computing
- Multilevel Inverters and Converters
- Neural Networks and Applications
- Machine Fault Diagnosis Techniques
- Chaos control and synchronization
- Microgrid Control and Optimization
- Iterative Learning Control Systems
- stochastic dynamics and bifurcation
- Nonlinear Dynamics and Pattern Formation
- Obstructive Sleep Apnea Research
- Adaptive Control of Nonlinear Systems
- Stability and Control of Uncertain Systems
- Advanced Control Systems Design
- Robotic Path Planning Algorithms
- Industrial Technology and Control Systems
- Smart Grid Energy Management
- Advanced DC-DC Converters
- Advanced Computational Techniques and Applications
Shanghai Jiao Tong University
2016-2025
Xi'an Jiaotong University
2010-2025
Air Force Engineering University
2006-2025
Fujian Agriculture and Forestry University
2025
Ruijin Hospital
2010-2024
Beijing University of Posts and Telecommunications
2015-2024
Baoji University of Arts and Sciences
2024
Shanghai Electric (China)
2024
Shanghai First People's Hospital
2018-2024
Taizhou University
2022-2024
Significance Breast cancer (BrCa) is the most common worldwide, and high-performance metabolic analysis emerging in diagnosis prognosis of BrCa. Here, we used nanoparticle-enhanced laser desorption/ionization mass spectrometry to record serum fingerprints BrCa seconds, achieving high reproducibility low consumption direct detection. Our analytical method, combined with aid machine learning algorithms, was demonstrated provide diagnostic efficiency accuracy 88.8% desirable prognostic...
With the rapid development of three-dimensional (3D) bioprinting technology, research revolving around in vitro functional pancreas and tumor models has become focus attention field life sciences. This review aims to summarize deeply discuss progress prospects 3D-bioprinted models. The efforts improving 3D printing technology increase its accuracy reliability biomedical applications have been ramped up over past few years. Researchers are now able create highly complex structures through...
This paper deals with the lag synchronization problem of memristor-based coupled neural networks or without parameter mismatch using two different algorithms. Firstly, we consider mismatch, complete cannot be achieved due to concept quasi-synchronization is introduced. Based on ω-measure method and generalized Halanay inequality, error level estimated, a new scheme proposed ensure that are in state an level. Secondly, by constructing Lyapunov functional applying common Halanary several...
Primary Sjogren's syndrome (pSS) is a slowly progressive, inflammatory autoimmune disease characterized by lymphocytic infiltration into salivary and lacrimal glands. It becomes more recognized that morphology alterations of epithelial mitochondria are involved in altered cellular bioenergetics pSS patients. The integrated analysis the mitochondrial role pathogenesis aberrant immune microenvironment remains unknown.The mitochondria-related genes gene expression data were downloaded from...
This paper is concerned with passivity and robust synchronisation of switched coupled neural networks uncertain parameters. First, the mathematical model interval parameters established, which consists L modes switches from one mode to another according switching rule. Second, by employing theory linear matrix inequality techniques, delay-independent delay-dependent conditions are derived guarantee networks. Moreover, based on proposed results, global criteria can be obtained for or without...
Congenital heart disease (CHD), the most common form of developmental abnormality in humans, remains a leading cause morbidity and mortality neonates.Genetic defects have been recognized as predominant causes CHD.Nevertheless, CHD is substantial genetic heterogeneity underlying cases remain unclear.In current study, coding regions splicing junction sites TBX20 gene, which encodes T-box transcription factor key to cardiovascular morphogenesis, were sequenced 175 unrelated patients with CHD,...
This paper is concerned with the problem of global exponential passivity for quaternion-valued memristor-based neural networks (QVMNNs) time-varying delay. The QVMNNs can be seen as a switched system due to memristor parameters are switching according states network. first time that delay investigated. By means nondecomposition method and structuring novel Lyapunov functional in form quaternion self-conjugate matrices, delay-dependent criteria derived forms linear matrix inequalities (LMIs)...
In this article, by introducing a signed graph to describe the coopetition interactions among network nodes, mathematical model of multiple memristor-based neural networks (MMNNs) with antagonistic is established. Since cooperative and competitive coexist, states MMNNs cannot reach complete synchronization. Instead, they will bipartite synchronization: all nodes' an identical absolute value but opposite sign. To synchronization, two kinds novel node- edge-based adaptive strategies are...
A unified distributed reinforcement learning (RL) solution is offered for both static and dynamic economic dispatch problems (EDPs). Each agent assigned with a fixed, discrete, virtual action set, projection method generates the feasible, actual actions to satisfy constraints. algorithm, based on singularly perturbed system, solves problem. form of Hysteretic Q-learning achieves coordination among agents. Therein, Q-values are developed actions, while rewards produced by projected actions....