9 Papers
28 Citations
Wei Wu is an academic researcher from Chinese Academy of Sciences. The author has contributed to research in topics: Graph theory & Communication channel. The author has an hindex of 3, co-authored 8 publications. Previous affiliations of Wei Wu include Hainan University.
Chat about Author
Papers
Channel resource allocation based on graph theory and coloring principle in cellular networks
Biyuan Yao,Jianhua Yin,Hui Li,Hui Zhou,Wei Wu +4 more
- 01 Apr 2018
TL;DR: In this work, the Hungarian algorithm is used to find the distribution scheme of the minimum probability of sub-channel detection in the cognitive terminal in the cellular network and it is shown that the division of distinguishable channels in channel allocation is necessary.
11
Network congestion control methods and theory
Wei Wu,Wencai Du,Guolong Ruan +2 more
TL;DR: The latest research on TCP/IP network congestion and control theory related to congestion control is introduced, different characteristics and control methods are analyzed and current challenges and future research directions are discussed.
9
Path Optimization Algorithms Based on Graph Theory
TL;DR: In this paper, the minimum cost and maximum flow result via classical iterative algorithm based on graph theory, adjacency matrix is well applied to express the relationship between transport nodes, a topological sorting transport map is adopted to verify these approaches.
State space representation and phase analysis of gradient descent optimizers
Biyuan Yao,Guiqing Li,Wei Wu +2 more
TL;DR: Experimental results show that selecting appropriate optimizers can accelerate the convergence speed of the model and improve the accuracy of model recognition, and the convergence speeds of the stochastic gradient descent-momentum and Nesterov accelerated gradient optimizers are better than those of theStellar gradient descent (SGD-M) and Nestersov acceleratedgradient (NAG) optimizers.
4
An Optimization Model on Virtual Machines Allocation Based on Radial Basis Function Neural Networks
TL;DR: A systemic method on virtual machine array optimization control based on artificial intelligence and matrix control theory to achieve low consumption optimization and ensure the stability of the system is presented.
3