Yangde Feng

Title: Innovations of Yangde Feng in Sparse Matrix Vector Multiplication

Introduction

Yangde Feng is a notable inventor based in Beijing, China. He has made significant contributions to the field of computational mathematics, particularly in the area of sparse matrix vector multiplication. His innovative approach has led to the development of a unique method that enhances the efficiency of this computational process.

Latest Patents

Yangde Feng holds a patent for a "Method and system for predicting operation time of sparse matrix vector multiplication." This patent describes a method that involves constructing a convolutional neural network with an input layer, a feature processing layer, a data splicing layer, and an output layer for generating prediction results. The method includes acquiring multiple groups of sparse matrices with known operation times as sample data, training the convolutional neural network with this data, and subsequently using the trained network to predict the operation time for new sparse matrices.

Career Highlights

Throughout his career, Yangde Feng has worked with prestigious institutions such as the China Institute of Atomic Energy and the Chinese Academy of Sciences. His work in these organizations has allowed him to apply his innovative ideas in practical settings, contributing to advancements in computational techniques.

Collaborations

Yangde Feng has collaborated with notable colleagues, including Jue Wang and Yangang Wang. Their joint efforts have furthered research and development in their respective fields.

Conclusion

Yangde Feng's contributions to the field of sparse matrix vector multiplication through his innovative patent demonstrate his expertise and commitment to advancing computational methods. His work continues to influence the landscape of mathematical computation.