ABSTRACT
This chapter describes the use of the least square approach to modeling, interference canceling, as well as the cases involving prediction. It examines the celebrated Wiener filter, which was developed during the Second World War. It also examines study another widely used filter known as the least mean squares (LMS) filter. It develops a class of linear optimum discrete-time filters known as the Wiener filters. The transmission of signals through space change, to a large extent, due to noise introduced by the change of the index of refraction and scattering elements of the atmosphere. The adaptive filtering algorithm continually varies the filter coefficients to reduce the mean square error toward its minimum value. Filtering of noisy signals is extremely important, and the method has been used in many applications, such as speech in a noisy environment, reception of data across a noisy channel, enhancement of images.
