Adaptive Filtering [Best of the Web]

This article focuses on adaptive filtering or, more generally, adaptive signal processing, the design of time-varying (adaptive) digital filters that would tune themselves to optimally process nonstationary signals in nonstationary environments. Least mean square (LMS) algorithm is widely used in adaptive signal processing, and is the most well-understood approach to training a linear system to minimize the mean square error. The second article described a recursive solution to the discrete-data linear filtering problem. Since that time, the Kalman filter has been the subject of extensive research and application. The area of adaptive signal processing has had a significant impact on a wide variety of signal processing applications.