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Tracking hypersonic glide reentry vehicles (HGRVs) is considered in the paper. Firstly, justified by an analysis of dynamic models of HGRVs, we proposed a more accurate motion model with less computation burden. Secondly, fixed-interval Gaussian mixture approximation smoother for non-linear Markov jump systems (NLMJSs) is presented in the paper. The Gaussian mixture filter can effectively approximate...
Estimation for discrete-time stochastic systems with parameters varying in a continuous space is considered in this paper. Justified by an analysis of model approximation, a novel approach, called hybrid grid multiple model (HGMM), is proposed for state estimation. The model set used by HGMM is a combination of a fixed coarse grid and an adaptive fine grid to cover the mode space with a relatively...
In this paper, a novel method is proposed to perform saliency detection in news video. This method comprises bottom-up attention model which considers low level features to produce bottom-up saliency map and top-down attention model which utilizes high level factors to generate top-down saliency map. In bottom-up attention model, color image is represented as quaternion. Then the quaternion discrete...
In this paper, a novel method is proposed to predict attention in image scenes by using a central stimuli sensitivity based saliency model. The proposed method is based on the general “center-surround” visual attention mechanism and the spatial frequency response of the human visual system (HVS). Following three biologically inspired principles, the saliency value is computed by two “scatter matrices”...
This paper considers the problem of state estimation for a hybrid system with Markovian switching parameters which belong to a continuous space. A hybrid grid multiple model (HGMM) estimator is presented. The total model set for HGMM is the combination of a fixed coarse grid and an adaptive fine grid. Three practical algorithms in this scheme are developed. These algorithms are used for state estimation...
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