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.