Vectorization of the DLMS transversal adaptive filter

• Published in: IEEE transactions on signal processing Vol. 42; no. 11; pp. 3237 - 3240
• Main Authors: Meyer, M.D., Agrawal, D.P.
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.11.1994; Institute of Electrical and Electronics Engineers
• Subjects: Adaptive filters; Algorithm design and analysis; Applied sciences; Clocks; Computational modeling; Concurrent computing; Delay; Detection, estimation, filtering, equalization, prediction; Exact sciences and technology; Information, signal and communications theory; Parallel algorithms; Performance analysis; Sampling methods; Signal and communications theory; Signal, noise; Telecommunications and information theory; Vectors; Parallel algorithm; Least squares method; Sampling rate; Transverse filter; Adaptive filter; Sampling; Vectorization
• ISSN: 1053-587X; 1941-0476
• DOI: 10.1109/78.330384

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.< >