Title :
Vectorization of the DLMS transversal adaptive filter
Author :
Meyer, Martin D. ; Agrawal, Dharma P.
Author_Institution :
Dept. of Electr. & Comput. Eng., Old Dominion Univ., Norfolk, VA, USA
fDate :
11/1/1994 12:00:00 AM
Abstract :
The subject of high sampling rate realizations for transversal adaptive filters is addressed. In particular, a vectorized version of the delayed least mean squares (DLMS) algorithm is derived using look-ahead computation techniques. The resulting parallel algorithm is then mapped onto a linear array of highly pipelined processing modules, which can accept an input vector of arbitrary length, and compute the corresponding output vector in a single clock cycle. The proposed system is shown to be capable of implementing transversal adaptive filters at sampling rates which are theoretically without bound. The performance of the proposed system is analyzed and simulation results are presented to verify the convergence properties of the algorithm under varying degrees of vectorization
Keywords :
adaptive filters; digital filters; least mean squares methods; parallel algorithms; parallel architectures; pipeline processing; DLMS transversal adaptive filter; convergence properties; delayed least mean squares algorithm; high sampling rate realizations; highly pipelined processing modules; input vector; linear array; look-ahead computation; output vector; parallel algorithm; performance; vectorization; Adaptive filters; Algorithm design and analysis; Clocks; Computational modeling; Concurrent computing; Delay; Parallel algorithms; Performance analysis; Sampling methods; Vectors;
Journal_Title :
Signal Processing, IEEE Transactions on