Title :
High speed RLS using scaled tangent rotations (STAR)
Author :
Raghunath, K.J. ; Parhi, Keshab K.
Author_Institution :
Dept. of Electr. Eng., Minnesota, Univ., Minneapolis, MN, USA
Abstract :
The QR decomposition based recursive least-squares (RLS) adaptive filtering algorithm (QRD-RLS) has a processing speed limitation. Fine-grain pipelining of the recursive loops within the cells using look-ahead techniques requires large hardware increase. A new scaled tangent rotation (STAR) is used instead of the usual Givens rotations. The scaled tangent rotation (STAR) RLS algorithm (STAR-RLS) is designed such that fine-grain pipelining can be accomplished very easily. The scaled tangent rotation are not exactly orthogonal transformations but tend to become orthogonal asymptotically. Simulation results show that the algorithm performance is similar to that of the QRD-RLS algorithm. The STAR-RLS algorithm can be mapped onto a systolic array. The computational complexity and inter cell communications are considerably lower than the QRD-RLS algorithm and the square-root free techniques
Keywords :
adaptive filters; computational complexity; digital filters; least squares approximations; pipeline processing; systolic arrays; Givens rotations; STAR-RLS algorithm; computational complexity; fine-grain pipelining; inter cell communications; look-ahead techniques; processing speed limitation; scaled tangent rotations; systolic array; Adaptive filters; Algorithm design and analysis; Computational complexity; Computational modeling; Estimation error; Filtering algorithms; Hardware; Pipeline processing; Resonance light scattering; Systolic arrays;
Conference_Titel :
Circuits and Systems, 1993., ISCAS '93, 1993 IEEE International Symposium on
Conference_Location :
Chicago, IL
Print_ISBN :
0-7803-1281-3
DOI :
10.1109/ISCAS.1993.394135