Variable step-size NLMS and affine projection algorithms

By Hyun-Chool Shin, Ali H. Sayed, Woo‐Jin Song. IEEE Signal Processing Letters, 2004

549 citations recorded by the source corpus.

This letter proposes two new variable step-size algorithms for normalized least mean square and affine projection. The proposed schemes lead to faster convergence rate and lower misadjustment error.

Subfields: Computational Mechanics, Signal Processing

View Paper: https://www.semanticscholar.org/paper/9b55dd1b3c5b7782fc7df0e2a1a9645ab1031526

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computational Mechanics

1. Ali H. Sayed
2. Jerónimo Arenas-García
3. Aníbal R. Figueiras-Vidal
4. Jacob Benesty
5. Federico S. Cattivelli
6. Jianshu Chen
7. Angelia Nedić
8. Alexander Olshevsky

In Signal Processing

1. Ali H. Sayed
2. Jerónimo Arenas-García
3. Aníbal R. Figueiras-Vidal
4. Jacob Benesty
5. Federico S. Cattivelli
6. Isao Yamada
7. Cássio Guimarães Lopes
8. Noriyuki Takahashi

Citations in the corpus

• A Nonparametric VSS NLMS Algorithm (2006, background): “Many different schemes have been proposed in the last two decades [5]–[12].”
• Mean-square performance of a convex combination of two adaptive filters (2006, background): “VARIABLE step-size adaptive filters allow the filters to dynamically adjust their performance in response to conditions in the input data and error signals [1]–[5].”