An improved model for the normalized LMS algorithm with Gaussian inputs and large number of coefficients

ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

Volumn 2, Issue , 2002, Pages

  Costa, Márcio H ^a   Bermudez, José C M ^a  

^a CATHOLIC UNIVERSITY OF PELOTAS   (Brazil)

Author keywords

[No Author keywords available]

Indexed keywords

ADAPTIVE ALGORITHMS; COMPUTER SIMULATION; GAUSSIAN NOISE (ELECTRONIC); MATHEMATICAL MODELS; MONTE CARLO METHODS;

GAUSSIAN INPUT; NORMALIZED LEAST MEAN SQUARE ALGORITHM;

ADAPTIVE FILTERING;

EID: 17444445873     PISSN: 15206149     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/icassp.2002.5745810     Document Type: Conference Paper

References (9)

1. A learning method for system identification
2. Analysis of the normalized LMS algorithm with Gaussian inputs
3. Convergence and performance analysis of the normalized LMS algorithm with uncorrelated Gaussian data
4. On the convergence behavior of the LMS and the normalized LMS algorithms
5. On the convergence rate performance of the normalized least-mean-square adaptation
6. On the independence theory of equalizer convergence
7. Fixed point error analysis of the normalized ladder algorithms