Least squares algorithms for adaptive linear-phase filtering

In many applications, it is desirable to use filters with linear-phase characteristics. This paper presents an approach for developing such filters for adaptive signal processing. Several least squares algorithms are derived for adjusting the coefficients of an adaptive linear phase filter. It is shown that smoothing filters, rather than the commonly used prediction filters, are a more natural choice if linear phase characteristics are required.