Papers
1
Total Citations
13
H-Index
1
About
Gh. Pana is a researcher whose work bridges the critical gap between neural network theory and real-time hardware implementation, with a particular focus on control systems and robotics. His most cited work, "Neural control based on RBF network implemented on FPGA" (2008, 13 citations), demonstrates his core contribution: the successful deployment of Radial Basis Function (RBF) networks on Field-Programmable Gate Arrays (FPGAs). This achievement is significant because it enables the high-speed, parallel processing capabilities of neural networks to be harnessed in applications where real-time performance is paramount, such as robotic control and industrial automation. By moving neural control from software simulation to dedicated hardware, Pana’s work addresses a fundamental challenge in embedded systems. His research is thus pivotal for engineers and scientists developing intelligent, responsive machines that must operate with minimal latency. While his citation count reflects a focused, technical audience, the impact of his work lies in its practical, enabling nature—providing a proven pathway for integrating advanced neural control into the physical world.
Research Focus
Key Achievements
Top Papers
- 1Neural control based on RBF network implemented on FPGA13 citations · 2008