Hangzhou, China

Kedi Xu


Average Co-Inventor Count = 5.0

ph-index = 1


Company Filing History:


Years Active: 2024

Loading Chart...
1 patent (USPTO):Explore Patents

Title: Kedi Xu - Innovator in Brain-Computer Interface Technology

Introduction

Kedi Xu is a prominent inventor based in Hangzhou, China. He has made significant contributions to the field of brain-computer interfaces, particularly through his innovative approaches to decoding methods. His work aims to enhance the interaction between humans and machines by improving the accuracy and stability of brain-computer systems.

Latest Patents

Kedi Xu holds a patent for an "Adaptive brain-computer interface decoding method based on multi-model dynamic integration." This invention discloses a method that improves traditional state-space models by utilizing a set of measurement functions. Instead of relying on a single fixed measurement function, this approach dynamically characterizes the relationship between observation variables and state variables. By employing a pool of linear and nonlinear decoders, the system can automatically switch decoders based on the data during the decoding process. This multi-model ensemble strategy integrates the capabilities of both linear and nonlinear decoders, thereby enhancing the accuracy and stability of brain-computer interface systems. It also addresses the decoding instability caused by non-stationary neural signals.

Career Highlights

Kedi Xu is affiliated with Zhejiang University, where he continues to advance research in brain-computer interface technology. His work has garnered attention for its innovative approach and practical applications in enhancing human-computer interaction.

Collaborations

Kedi Xu collaborates with notable colleagues, including Yu Qi and Yueming Wang, who contribute to his research endeavors and help drive advancements in the field.

Conclusion

Kedi Xu's contributions to brain-computer interface technology exemplify the potential of innovative thinking in solving complex problems. His adaptive decoding method represents a significant step forward in the development of more effective brain-computer systems.

This text is generated by artificial intelligence and may not be accurate.
Please report any incorrect information to support@idiyas.com
Loading…