This paper aims to investigate several new nonlinear/non-Gaussian filters in the context of the sequential data assimilation. The unscentedKalman filter (UKF), the ensemble Kalman filter (EnKF), the sampling importance resampling particle filter (SIR-PF) and the unscented particle filter (UPF) are described in the state-space model framework in the Bayesian filtering background. We first evalua...

Measles virus (MV) infects a variety of lymphoid and non-lymphoid peripheral organs. However, in rare cases, the virus can persistently infect cells within the central nervous system. Although some of the factors that allow MV to persist are known, the contribution of host cell-encoded microRNAs (miRNA) have not been described. MiRNAs are a class of noncoding RNAs transcribed from genomes of al...

Let K ⊂ R d be a convex body, and assume that L is randomly rotated shifted integer lattice. the hull of (random) points ∩ . The mean width W ( ) investigated. asymptotic order difference λ − maximized by obtained polytopes minimized for smooth sets as → ∞

Satellites provide various services essential to the modern life of human being. For example, satellite images are used for many applications such as reconnaissance, geographic information system, etc. Therefore, design and operation requirements of the satellite system have become more severe, and also the system reliability during the operation is required. Satellite attitude control systems ...

The Extended Kalman Filter (EKF) has become a standard technique used in a number of nonlinear estimation and machine learning applications. These include estimating the state of a nonlinear dynamic system, estimating parameters for nonlinear system identification (e.g., learning the weights of a neural network), and dual estimation (e.g., the ExpectationMaximization (EM) algorithm)where both s...

The univariate non-stationary growth model (UNGM) is widely used in the verification of nonlinear filters, and unscented Kalman filter (UKF) often as reference for comparative analysis when using this to evaluate performance. However, due strong nonlinearity UNGM change properties with different parameter settings, estimation misalignment problem reasons will occur UKF filtering. To solve these...

A convergence analysis of the modified unscented Kalman filter (UKF), used as an observer for a class nonlinear deterministic continuous time systems, is presented. Under certain conditions, extended (EKF) exponential non-linear i.e., dynamics estimation error exponentially stable. It shown that unlike EKF, UKF not converging observer. modification – proposed, which better candidate This paper ...