The time-frequency spectrograms associated with the same dynamic hand gesture are modeled by a hidden Gauss-Markov model (HGMM), and the testing gesture is recognized by the maximum likelihood ...

Therefore, this paper combs the related factors that affect the epidemic risk, and proposes an epidemic risk assessment model based on 12 indicators by combining Markov chain and AHP. The model can ...

Abstract: This paper presents a semi-Markov decision process (SMDP) formulation of the satellite task scheduling problem. This formulation can consider multiple operational objectives simultaneously ...

Abstract: This paper proposes a simulation-based algorithm for optimizing the average reward in a finite-state Markov reward process that depends on a set of parameters. As a special case, the method ...

Similar to other control systems, the subsystems in MJSs are usually described by some type of dynamic equations, while a Markov process that can be either continuous time or discrete time describes ...

Abstract: This paper focuses on the state feedback stabilization problem for a class of discrete-time singular Markov jump systems with repeated scalar nonlinearities. First, on the basis of the ...

Abstract: This article investigates the problem of state estimation for guarded semi-Markov switching systems with soft constraints. We first construct the switching system in a multiple model manner ...

Abstract: This paper presents a new approach for automatic recognition of gait phases based on the use of an in-shoe pressure measurement system and a multiple-regression hidden Markov model (MRHMM) ...

Natilus, also known as the 'Boeing killer', is redefining the skyscape with its blended-wing-body planes. According to CEO, Aleksey Matyushev, consumers can expect to step aboard within the next ...

Abstract: This article investigates the adaptive fuzzy asynchronous control problem for discrete-time nonhomogeneous Markov jump power systems under hybrid attacks. A nonhomogeneous Markov process is ...

In this paper, we have proposed a novel SOH estimation method by using a prior knowledge-based neural network (PKNN) and the Markov chain for a single LIB. First, we extract multiple features to ...