The recursive least square lattice (LSL) algorithm based on the newly developed scaled tangent rotations (STAR) is derived. Similar to other recursive least square lattice algorithms for adaptive filtering, this algorithm requires only O(N) operations. This algorithm also preserves the desired properties of the STAR recursive least square (STAR-RLS) algorithm. Specifically, it can be pipelined at fine-grain level. To this end, a pipelined version of the STAR-LSL (referred to as PSTAR-LSL) is also developed. Computer simulations show that the performance of the STAR-LSL algorithm is as good as the QRD-LSL algorithm. The finite precision error properties of the STAR-LSL algorithm are also analyzed. The mean square error expressions show that the numerical error propagates from stage to stage in the lattice, and the numerical error of different quantities in the algorithm varies differently with A. This suggests that different word lengths need to be assigned to different variables in the algorithm for best performance. Finally, finite word length simulations are carried out to compare the performances of different topologies.
|Original language||English (US)|
|Number of pages||15|
|Journal||IEEE Transactions on Circuits and Systems II: Analog and Digital Signal Processing|
|State||Published - 1997|
Bibliographical noteFunding Information:
Manuscript received March 15, 1996; revised August 26, 1996. This work was supported by the Army Research Office under Contract DA/DAAH 04-94-G-0405 and NEC Corporation. This paper was recommended by Associate Editor B. A. Shenoi.
- Finite word length analysis
- Givens rotation
- Lattice structures
- RLS adaptive filtering
- STAR rotation