Usually databases are treated primarily as fairly dumb data storage systems, but they can be capable of much more. Case in ...

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 we are hiring someone such as a carpenter or an auto mechanic, we always look for two things: what kind of tools they have and what they do when things go wrong. For many types of embedded systems, ...

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

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 ...

Kalman filter models based on the assumption of multivariate Gaussian distributions are known to be nonrobust. This means that when a large discrepancy arises between the prior distribution and the ...

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 ...

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 ...

In this course, you will learn how to implement different state-of-charge estimation methods and to evaluate their relative merits. Prior knowledge needed: ECEA 5730, ECEA 5731, a Bachelor’s degree in ...