In this paper, adaptive sensor fusion INS/GNSS is proposed to solve specific problem of non linear time variant state space estimation with measurement outliers, different algorithms are used to solve this specific problem generally occurs in intentional and non-intentional interferences caused by other radio navigation sources, or by the GNSS receiver’s deterioration. Non linear approximation ...

Sequential Bayesian filters in non-linear dynamic systems require the recursive estimation of predictive and posterior probability density function (pdf). This paper introduces a filter called adaptive kernel Kalman (AKKF). The AKKF approximates arbitrary pdf hidden states using mean embedding (KME) reproducing Hilbert space (RKHS). In parallel with KME, some particles data are used to capture ...

Abstract Aiming at the problem of rapid transfer alignment inertial navigation system in shipborne environment with large azimuth misalignment angle, a dimension reduction fast scheme aircraft based on CKF algorithm is designed. Firstly, nonlinear attitude error equation, velocity equation and position Global Navigation Satellite System (GNSS) assisted strapdown case are analyzed. Secondly, dim...

One of the most important problems when designing controller is how to deal with all kinds of uncertainties, which, along with the high nonlinearities of most real systems, makes it difficult to guarantee the desired closed loop performance. Recently, nonlinear Kalman-class filter has been extensively researched and several well-known algorithms, including Extended Kalman Filter (EKF), Unscente...

BACKGROUND Ellipticine and doxorubicin are antineoplastic agents, whose action is based mainly on DNA damage such as intercalation, inhibition of topoisomerase II and formation of covalent DNA adducts. The key target to resolve which of these mechanisms are responsible for ellipticine and doxorubicin anticancer effects is the development of suitable methods for identifying their individual DNA-...

[1] A dual unscented Kalman filter (UKF) was used to assimilate net CO2 exchange (NEE) data measured over a spruce-hemlock forest at the Howland AmeriFlux site in Maine, USA, into a simple physiological model for the purpose of filling gaps in an eddy flux time series. In addition to filling gaps in the measurement record, the UKF approach provides continuous estimates of model parameters and u...

Data assimilation is a valuable tool in the study of any complex system, where measurements are incomplete, uncertain, or both. It enables the user to take advantage of all available information including experimental measurements and short-term model forecasts of a system. Although data assimilation has been used to study other biological systems, the study of the sleep-wake regulatory network...

Neuroblastoma is a tumor accounting for approximately 10% of all childhood malignancies and 50% of all childhood cancer-related deaths. MYCN gene copy number variation represents the most important prognostic factor in neuroblastoma. Prognostic significance of MYCN gene expression is more complicated and may depend on other factors such as MYCN gene copy number status. In the present study, we ...

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...