Title :
Efficient recursive least-squares adaptive quadratic filters
Author :
Davila, Carlos E.
Author_Institution :
Dept. of Electr. Eng., Southern Methodist Univ., Dallas, TX, USA
Abstract :
A recursive least-squares algorithm for the quadratic filter is described which has satisfactory convergence for larger filter lengths while maintaining low computational requirements. A similar least-mean-square (LMS) algorithm is also described. The respective algorithms are based on the so-called normalized recursive least-squares and normalized LMS algorithms and have considerably better performance than their unnormalized counterparts.<>
Keywords :
adaptive filters; filtering and prediction theory; least squares approximations; low computational requirements; normalized LMS algorithms; normalized recursive least-squares; recursive least-squares adaptive quadratic filters; Adaptive filters; Filtering; Least squares methods; Prediction methods;
Conference_Titel :
Systems Engineering, 1989., IEEE International Conference on
Conference_Location :
Fairborn, OH, USA
DOI :
10.1109/ICSYSE.1989.48696
