ALGORITMOS LMS DE FILTRADO ADAPTATIVO PARA CANCELACIÓN DE ECO ACÚSTICO EN SISTEMAS DE TELECOMUNICACIONES
DOI:
https://doi.org/10.24054/rcta.v1i23.1876Palabras clave:
Cancelador de eco acústico, lgoritmo de mínimos cuadrados promediados LMS, filtros adaptablesResumen
Este trabajo se centra en el estudio y la comparación de las características de modelado, simulación y desempeño de filtros adaptativos LMS utilizados para aplicaciones de cancelación de eco. En ese sentido, tres algoritmos de filtrado adaptativo
convencionales se revisan, el algoritmo de Mínimos Cuadrados Promediados Convencional (LMS), el algoritmo LMS Normalizado (NLMS) y el algoritmo LMS signado (SLMS). Por último, la comparación entre los algoritmos se evaluó mediante índices de desempeño tales como respuesta temporal, velocidad de convergencia y análisis espectral ERLE.
Descargas
Citas
Adali, T. and Haykin, S. (2010). Adaptive and
Learning Systems for Signal Processing,
Communications, and Control, John Wiley &
Sons.
Asjadi, H. and Ababafha, M. (1997). “Adaptive
Echo Cancellation Based On Third Order
Cumulant, International Conference on
Information, Communications and Signal
Processing, ICICS '97 Singapore, Sept. 1997.
Bellanger, M. (2001). Adaptive Digital Filters and
Signal Analysis, Marcel Deckr, New York
nd Edition.
Breining, C., Dreiseitel, P., Hansler, E., Mader, A.,
Nitsch, B.,Puder, H., Schertler, T., Schmidt,
G., and Tilp, J. (1999). “Acoustic Echo
Control”. IEEE Signal Proc. Magazine, 16, 42
– 69.
Cuenca, D. y Muñoz. A. (2005). Control Activo de
Ruido. Universidad de Costa Rica.
Diniz, P. S. (2008). Adaptive Filtering: Algorithms
and Practical Implementation. 3rd edition
Springer, New York, NY, USA.
Duttweiler, D. L., (2000). “Proportionate
normalized least mean square adaptation in
echo cancellers”, IEEE Transactions on
Speech and Audio Processing, Vol. 8, pp.
–518, Sept. 2000.
Duttweiler, D.L. (2000). “Proportionate
Normalized Least Mean Square Adaptation in
Echo Cancellers,” IEEE Trans. Speech Audio
Processing, vol. 8, pp. 508-518, Sept. 2000.
Eneman, K. and Moonen, M. (2003). “Iterated
partitioned block frequency-domain adaptive
filtering for acoustic echo cancellation,” IEEE
Transactions on Speech and Audio
Processing, vol. 11, pp. 143-158, Mar. 2003.
Gay, S. L. and Benesty, J. (2000). Acoustic Signal
Processing for Telecommunication. Kluwer
Academic Publishers, Boston, MA.
Haykin, S. (2013). Adaptive Filter Theory, Pearson
Education, Prentice Hall. 5th Edition.
Jamel, T. (2013). “Performance Enhancement of
Adaptive Acoustic Echo Canceller Using a
New Time Varying Step Size LMS Algorithm
(NVSSLMS)”. International Journal of
Advancements in Computing Technology
(IJACT), Korea , Vol. 3, No. 1, Jan. 2013.
Krishna, E.H.; Raghuram, M.; Madhav, K.V and
Reddy, K.A. (2010). “Acoustic echo
cancellation using a computationally efficient
transform domain LMS adaptive filter,” 2010
th International Conference on Information
sciences signal processing and their
applications (ISSPA), pp. 409-412, May.
Kuch, F. (2005). Adaptive Polynomial Filters and
their Application to Nonlinear Acoustic Echo
Cancellation. PhD thesis, Der Technischen
Fakult¨at der Friedrich-Alexander-
Universit¨at Erlangen-N¨urnberg, Germany.
Lankila, A. (2008). Simulation Model for an Active
Noise Control System - Development and
Validation. Helsinki University Of
Technology. Espoo.
Makino, S., Kaneda, Y. and Koizumi, N. (1993).
“Exponentially weighted step size NLMS
adaptive filter based on the statistics of a
room impulse response”, IEEE Trans. on speech and audio Processing, vol. 1, No.1,
pp.101-108, Jan 1993.
Manikandan, S. Mythili, S. (2006). Improved
active noise feedforward control systems
using delta rule algorithm. Dept of ECE,
KSR College of Tech, ANNA University,
Tamilnadu, India. ISSN 1311-4360. Volume
, 2006.
Meler, L. (2005). Variantes del Algoritmo LMS.
Aplicación a un Sistema Cancelador de Ecos.
Escuela Universitaria Politécnica de Teruel.
Universidad de Zaragoza.
Muñoz, E.A. y Tapia, X. A. (2007). Diseño e
Implementación de un Sistema de Reducción
del Ruido Industrial en la Comunicación
entre Operadores. Escuela Politécnica
Nacional.
Olivares, A. P. (2001). Desarrollo de un Prototipo
de Control Activo de Ruido Utilizando el DSP
de Punto Flotante TMS320C31. Instituto
Tecnológico y de estudios superiores de
Monterrey.
Paleologu, C.; Benesty, J.; Grant, S.L. aand
Osterwise, C. (2009). “Variable step-size
NLMS algorithms for echo cancellation”
Conference Record of the forty-third
Asilomar Conference on Signals, Systems and
Computers, pp. 633-637, Nov 2009.
Per Ahgren, (2004). An environment for real time
laboratory exercises in acoustic echo
cancellation, Ph.D. Dissertation, Department
of systems and control, Uppsala University,
Uppsala, Sweden.
Poularikas, D. and Ramadan, Z. (2006). Adaptve
Filtering Primer with MATLAB, CRC Press.
Sayed, A. (2008). Adaptve Filters, John Wiley &
Sons.
Stearns, S. D. and Widrow, B. (1985) Adaptive
Signal Processing, Prentice-Hall, Inc.
Englewood Cliffs, N.J, 1985.
Velazquez, J., Sanchez, J. y Perez, H. (2006).
“Adaptive filters with codified error LMS
Algorithm”, International Journal
Electromagnetic Waves and Electronic
Systems, Vol. 1, pp. 23 – 28, Jul. 2006.
Widrow, B. and Hoff, M. E. (1960). Adaptive
Switching Circuits, IRE Wescon Conv.Rec.,
pt. 4, pp. 96 – 104.
Zhao, H.; Hu, S.; Li, L. and Wan, X. (2013).
“NLMS Adaptive FIR Filter Design Method”,
IEEE Region 10 Conference TENCON,
pp. 1- 5.
Zhao, L., Hu, S., Li, L. and Wan, X. (2013).
“Implementation of Recursive Least Squares
(SLMS) Adaptive Filter for Noise
Cancellation”. International Journal of
Scientific Engineering and Technology. Vol.
No.1, Issue No.4, pp. 46-48.
Descargas
Publicado
Versiones
- 2014-01-02 (4)
- 2014-01-02 (3)
- 2014-01-02 (2)
- 2022-11-08 (1)
Cómo citar
Número
Sección
Licencia
Derechos de autor 2022 REVISTA COLOMBIANA DE TECNOLOGIAS DE AVANZADA (RCTA)
Esta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial 4.0.
