Background. Seasonal influenza can cause severe health problems and significant economic burdens in various regions of the world. In addition to the substantial morbidity and mortality cases caused by influenza, the emergency department crowding is also partially attributed to the influenza patients. Forecasting the influenza trends is crucial in developing effective countermeasures to mitigate...

Kalman filtering has been extensively used technique to estimate the states of discrete-time dynamic systems in a wide range of applications such as control system, signal processing and communication systems etc. A correct and accurate state estimation of linear or non-linear system can be improved by selecting the proper estimation technique. State estimation can be improved by linearizing th...

In this paper, a new robust extended Kalman filtering algorithm based on singular value decomposition (SVD) of covariance / information matrix is presented with application in the flight state and parameter estimation of aircraft. The presented algorithm not only has a good numerical stability but also can handle correlated measurement noise without any additional transformation. The algorithm ...

Combined state and parameter estimation of dynamical systems plays a crucial role in extracting system response from noisy measurements. A wide variety of methods have been developed to deal with the joint state-parameter estimation of nonlinear dynamical systems. The Extended Kalman Filter method is a popular approach for the joint systemparameter estimation of nonlinear systems. This method c...

Current out-of-sequence measurement (OOSM) filtering algorithms belong to two distinct classes, Kalman filter (KF) or extended KF (EKF) based and particle filter (PF) based. This paper compares the performances of the multiple-lag KF and PF based OOSM filtering algorithms for a number of scenarios with linear dynamic and measurement models with additive Gaussian noises first. The KF with in-seq...

[l] R. E. Kalman, “A new approach to linear filtering and prediction problems,” J. Basic Eng., Tram. ASME, pp. 35-45, Mar. 1960. [2] C. K. Chui and G. Chen, Kalrnun Filtering with Real-Time Applications. New York: Springer-Verlag. 1987. [3] L. Ljung, “Asymptotic behavior of the extended Kalman filter as a parameter estimator for linear systems,” IEEE Trans. Automat. Conrr., vol. 24, no. 1. pp. ...

A nonlinear semi-analytic filtering method to sequentially estimate spacecraft states and their associated uncertainties is presented. We first discuss the state transition tensors that characterize the localized nonlinear behavior of the spacecraft trajectory and illustrate the importance of higher order effects on orbit uncertainty propagation. We then present the semi-analytic filtering meth...

Nonlinear semi-analytic filtering methods to sequentially estimate spacecraft states and their associated uncertainties are presented. We first discuss the state transition tensors that characterize the localized nonlinear behavior of the trajectory statistics and illustrate the importance of higher-order effects on orbit uncertainty propagation. We then present a semi-analytic filtering method...