A comprehensive review of extreme learning machine on medical imaging
The feedforward neural network based on randomization has been of great interest in the
scientific community, particularly extreme learning machines, due to its simplicity, training …
scientific community, particularly extreme learning machines, due to its simplicity, training …
Asymmetric cooperation control of dual-arm exoskeletons using human collaborative manipulation models
The exoskeleton is mainly used by subjects who suffer muscle injury to enhance motor
ability in the daily life environment. Previous research seldom considers extending human …
ability in the daily life environment. Previous research seldom considers extending human …
MFRFNN: Multi-functional recurrent fuzzy neural network for chaotic time series prediction
Chaotic time series prediction, a challenging research topic in dynamic system modeling,
has drawn great attention from researchers around the world. In recent years extensive …
has drawn great attention from researchers around the world. In recent years extensive …
A novel representation learning for dynamic graphs based on graph convolutional networks
C Gao, J Zhu, F Zhang, Z Wang… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Graph representation learning has re-emerged as a fascinating research topic due to the
successful application of graph convolutional networks (GCNs) for graphs and inspires …
successful application of graph convolutional networks (GCNs) for graphs and inspires …
A learning-based stable servo control strategy using broad learning system applied for microrobotic control
As the controller parameter adjustment process is simplified significantly by using learning
algorithms, the studies about learning-based control attract a lot of interest in recent years …
algorithms, the studies about learning-based control attract a lot of interest in recent years …
Adaptive neural-network-based fault-tolerant control for a flexible string with composite disturbance observer and input constraints
Z Zhao, Y Ren, C Mu, T Zou… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
We propose an adaptive neural-network-based fault-tolerant control scheme for a flexible
string considering the input constraint, actuator gain fault, and external disturbances. First …
string considering the input constraint, actuator gain fault, and external disturbances. First …
Hierarchical dynamic graph convolutional network with interpretability for EEG-based emotion recognition
Graph convolutional networks (GCNs) have shown great prowess in learning topological
relationships among electroencephalogram (EEG) channels for EEG-based emotion …
relationships among electroencephalogram (EEG) channels for EEG-based emotion …
Cross-cultural emotion recognition with EEG and eye movement signals based on multiple stacked broad learning system
With increasing social globalization, interaction between people from different cultures has
become more frequent. However, there are significant differences in the expression and …
become more frequent. However, there are significant differences in the expression and …
Industrial big data-driven mechanical performance prediction for hot-rolling steel using lower upper bound estimation method
Industrial big data technology has become one of the important driving forces to intelligent
manufacturing in the steel industry. In this study, the characteristics of data in steel …
manufacturing in the steel industry. In this study, the characteristics of data in steel …
GPU-free specific emitter identification using signal feature embedded broad learning
Emerging wireless networks may suffer severe security threats due to the ubiquitous access
of massive wireless devices. Specific emitter identification (SEI) is considered as one of the …
of massive wireless devices. Specific emitter identification (SEI) is considered as one of the …