Optimal control: linear quadratic methods
Optimal control: linear quadratic methods
Sampling in digital signal processing and control
Sampling in digital signal processing and control
Digital Control and Estimation: A Unified Approach
Digital Control and Estimation: A Unified Approach
On sequential Monte Carlo sampling methods for Bayesian filtering
Statistics and Computing
Constrained Control and Estimation: An Optimisation Approach
Constrained Control and Estimation: An Optimisation Approach
A survey of convergence results on particle filtering methods forpractitioners
IEEE Transactions on Signal Processing
Brief Constrained linear state estimation-a moving horizon approach
Automatica (Journal of IFAC)
| Hi-index | 22.14 |
One of the most commonly used tools in systems science is that of nonlinear filtering. Applications can be found in control engineering, telecommunications, radar tracking, environmental systems, economics and many other areas. The goal of this paper is to contribute to the application of nonlinear filtering theory by presenting insights into the role of temporal sampling especially the use of up-sampling and down-sampling.