ABSTRACT
The process of estimation involves integrating information over time, and effective ways of performing this process have much in common with the behaviors involved in actually exerting control. This chapter explores some simple examples to perform Lag-Like calculations. An optimal estimator is a computational algorithm that processes measurements to deduce a minimum error estimate of the state of a system by utilizing: knowledge of system and measurement dynamics, assumed statistics of system noises and measurement errors, and initial condition information. The weighting of the difference between the observation and the estimated output of the lag will gradually decrease over time, in analogy with the first recursive calculation of the mean. If the mean and variance of the Gaussian process remain constant, then the aforementioned scheme provides a very efficient estimate of that mean.
