Kalman filtering has emerged as a pivotal tool in the field of multibody system dynamics, offering a robust framework for real-time state and parameter estimation in systems composed of interconnected ...

If you program using values that represent anything in the real world, you have probably at least heard of the Kalman filter. The filter allows you to take multiple value estimates and process them ...

Kalman filtering has long served as a foundational tool for state estimation in dynamic systems, offering a robust and efficient means of filtering noise from measured signals. In the realm of ...

It appears that no particular approximate [nonlinear] filter is consistently better than any other, though . . . any nonlinear filter is better than a strictly linear one. 1 The Kalman filter is a ...

Numerical basics -- Method of least squares -- Recursive least-quares filtering -- Polynomial Kalman filters -- Kalman filters in a nonpolynomial world -- Continuous polynomial Kalman filter -- ...

This is an expository article that develops the Kalman filter from a Cholesky factorization perspective. In particular, the Kalman filter is shown to be a modification of the Cholesky factorization ...

In practical situations, we observe the number of claims to an insurance portfolio but not the claim intensity. It is therefore of interest to try to solve the 'filtering problem'; that is, to obtain ...

EnSilica, a leading independent provider of semiconductor solutions and IP, has launched a Kalman Filter acceleration IP core for use in situational awareness radar sensors for advanced driver ...

This paper proposes a new econometric model for the estimation of optimal hedge ratios (HRs): the Kalman filter error-correction model (KF–ECM). This paper proposes a new econometric model for the ...