In signal processing, the Wiener filter is a filter (signal processing)|filter proposed by Norbert Wiener during the 1940s and published in 1949. Its purpose is to reduce the amount of noise present in a signal by comparison with an estimation of the desired noiseless signal. The discrete-time equivalent of Wiener's work was derived independently by Andrey Kolmogorov and published in 1941. Hence the theory is often called the Wiener-Kolmogorov filtering theory. The Wiener-Kolmogorov was the first statistically designed filter to be proposed and subsequently gave rise to many others including the famous Kalman filter. A Wiener filter is not an adaptive filter because the theory behind this filter assumes that the inputs are Stationary process|stationary.