Yoo Hsiu Yeh
Papers
1
Total Citations
3
H-Index
1
About
Yoo Hsiu Yeh’s research centers on intelligent control systems, neural networks, and robotics, with a particular emphasis on adaptive and self-organizing algorithms. Her most cited work, “Robot control with a fully tuned Growing Radial Basis Function neural network” (2011), introduces a novel GRBF controller that dynamically adjusts not only network weights but also centers and standard deviations in real time, enabling more precise and flexible robot manipulator control. This contribution is notable for its online adaptation and node-growing capability, which allows the system to expand its architecture as needed—a key advancement in autonomous robotic learning. While her citation count is modest, the work demonstrates foundational thinking in adaptive neural control, laying groundwork for future research in self-tuning robotic systems. Yeh’s approach reflects a deep commitment to bridging theoretical neural network design with practical, real-time robotic applications, making her a thoughtful contributor to the field of intelligent control.
Research Focus
Key Achievements
Top Papers
- 1