This paper studies the problem of positive 1 state-bounding observer design for a class of positive Markovian jump systems with interval parameter uncertainties by a linear programming approach. For the first, necessary and sufficient conditions are obtained for stochastic stability and 1 performance of positive Markovian jump systems by an "equivalent" deterministic positive linear system. Furthermore, based on the results obtained in this paper, sufficient conditions for the existence of the positive 1 statebounding observer are derived. The conditions can be solved in terms of linear programming. Finally, a numerical example is used to illustrate the effectiveness of the results obtained.

Augmented reality (AR) is a technology based on 3D registration, virtual-real fusion and human-computer interaction to achieve the integration of virtual objects and real scenes. The core problem of augmented reality task is the accurate and fast recognition and tracking of objects in real scenes, which provides the technical basis for updating and optimizing the selfie design. This paper discusses the specific technical path of AR applied to selfie design based on the deep learning approach, and demonstrates the impact of different deep learning algorithms on the effectiveness of the integration of AR and selfie, and finally the paper discusses the application prospects of AR in selfie.