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The blast furnace gas is an important secondary energy for the iron and steel production. Establishing an effective model to describe the state of BFG system is of great significant to maintain the system balance and stability. Considering the strong coupling characteristics of the blast furnace gas system and the high level noises in the industrial data, a simplex unscented Kalman filter-based Wang-Mendel...
This paper addresses the maneuvering target tracking (MTT) problems for linear discrete-time dynamic systems with multiple models. A generalized formulation of the multiple-model (MM) dynamic systems is proposed, and a new treatment called random parameters Kalman filtering (RPKF) is investigated. The random parameters including some coefficient matrices and noise covariances are used to characterize...
This paper is concerned with the sparse signal recovery problem in sensor networks, and the main purpose is to design a filter for each sensor node to estimate a sparse signal sequence using the measurements distributed over the whole network. A so-called ℓ1-regularized H∞ filter is established at first by introducing a pseudo-measurement equation, and the necessary and sufficient condition for existence...
PaaS is one of the most popular paradigms of cloud computing and the performance guarantee of PaaS-oriented applications has been critically concerned. Performance models, such as a Layer Queue Network (LQN) model, are efficient at performance guaranteeing in a highly dynamic computing environment for their capabilities of capacity planning. However, it is not a trivial work to build and employ such...
It is important to maintain the identity of multiple targets while tracking them in some applications such as behavior understanding. However, unsatisfying tracking results may be produced due to different real-time conditions. These conditions include: inter-object occlusion, occlusion of the ocjects by background obstacles, splits and merges, which are observed when objects are being tracked in...
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