Kun Chen Hu

Learn More
Rework cycle is at the heart of modeling projects, one of the major application areas of system dynamics. In this paper we introduce a new formulation for rework cycle in which multiple defects may exist in a task. We compare the performance of this model with three other formulations, two adopted from system dynamics literature and one agent-based(More)
We are witnessing a revolution in wireless technology where Light Fidelity (LiFi) emerges as one potential candidate. In this paper we present a LiFi prototype that allows us to verify the feasibility of deploying this technology. The prototype is based on two Spartan 6 FPGAs and uses a Light Emitting Diode (LED) to transport the information through(More)
We study the application of reputation as an instigator of beneficial user behavior in selfish routing and when the network users rely on the network coordinator for information about the network. Instead of using tolls or artificial delays, the network coordinator takes advantage of the users' insufficient data, in order to manipulate them through the(More)
An improved method of hierarchical reinforcement learning which named BMAXQ was presented in order to resolve the shortcomings of MAXQ. It amended the abstract mechanism of MAXQ and utilized the peculiarities of BP neural network. This method can make agent to find the subtasks automatically and realize parallel learning for every layer. It can be adapted(More)
This paper mainly deals with the almost surely exponential stability and exponential p-th moment stability for a class of stochastic Cohen–Grossberg neural networks with distributed delays and reaction–diffusion term. By constructing suitable Lyapunov functional, employing the nonnegative semi-martingale convergence theorem and applying matrix theory and(More)
  • 1