An Optimization Theory for Time-Varying Linear Systems with Nonstationary Statistical Inputs

The mean-square optimization problem is stated for time-varying systems with nonstationary statistical input functions. Correlation functions are defined for nonstationary ensembles. The mean-square error is calculated in terms of these correlation functions. The integral equation defining the optimum system is determined by minimization of the mean-square error.