In principle either approach allows one to estimate a quantity function (the state of a dynamical system) from noisy measurements, even when the system is non-linear (thus generalizing the earlier results of Wiener and Kalman for linear systems and solving a central problem in estimation theory).
Both approaches allow for estimating a quantity function (the state of a dynamical system) based on noisy data, applicable to both linear and nonlinear systems. This capability extends beyond the original work by Wiener and Kalman and solves a key problem in estimation theory.