In this paper, we propose a set of algorithms to design signal timing plans via deep reinforcement learning. The core idea of this approach is to set up a deep
This paper proposes a Graph regularized Lpsmooth non-negative matrix factorization(GSNMF) method by incorporating graph regularization and Lp smoothing constrai
This paper focuses on the delay-dependent stability for a kind of Markovian jump time-delay systems(MJTDSs),whose transition rates are incompletely known. In or
In this paper, the finite-time attitude tracking control problem for the spacecrafts with variable tilt of flexible appendages in the conditions of exogenous di
Motion planning is one of the most significant technologies for autonomous driving. To make motion planning models able to learn from the environment and to dea
In the past decade, existing and new knowledge and datasets have been encoded in different ontologies for semantic web and biomedical research. The size of onto