TY - GEN
T1 - Convex combination of FXECAP- FXECLMS algorithms for active noise control
AU - Rodriguez, J.
AU - Ibarra, I.
AU - Pichardo, E.
AU - Avalos, J. G.
AU - Sanchez, J. C.
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/7/2
Y1 - 2018/7/2
N2 - Adaptive algorithms used for active noise control systems require a high convergence speed in order to be usable in real ANC applications. Affine projection (AP) algorithms offer a high convergence rate, however, this speed entails a high misadjustment. AP algorithms have been combined with other algorithms to address this misadjustment level, these combinations are known as a convex combination. However, such combinations tend to be computationally complex which precludes them from being used in ANC applications. This work presents a new convex combination, composed of the Filtered-x Error Coded Affine Projection and the Filtered-x Error Coded Least Mean Square Algorithm (CC FXECAP-FXECLMS), with the aim of obtaining an algorithm that retains the speed of the AP while achieving misadjustment levels of the LMS, while at the same time producing an algorithm with a computational complexity low enough to be practical for use in real ANC applications. Test results have confirmed the algorithm's capabilities and proven that the algorithm is suitable for this role.
AB - Adaptive algorithms used for active noise control systems require a high convergence speed in order to be usable in real ANC applications. Affine projection (AP) algorithms offer a high convergence rate, however, this speed entails a high misadjustment. AP algorithms have been combined with other algorithms to address this misadjustment level, these combinations are known as a convex combination. However, such combinations tend to be computationally complex which precludes them from being used in ANC applications. This work presents a new convex combination, composed of the Filtered-x Error Coded Affine Projection and the Filtered-x Error Coded Least Mean Square Algorithm (CC FXECAP-FXECLMS), with the aim of obtaining an algorithm that retains the speed of the AP while achieving misadjustment levels of the LMS, while at the same time producing an algorithm with a computational complexity low enough to be practical for use in real ANC applications. Test results have confirmed the algorithm's capabilities and proven that the algorithm is suitable for this role.
KW - Active noise control
KW - Convex combination of adaptive filters
KW - Error coded affine projection algorithm
KW - Error coded least mean square
UR - http://www.scopus.com/inward/record.url?scp=85063898927&partnerID=8YFLogxK
U2 - 10.1109/ROPEC.2018.8661379
DO - 10.1109/ROPEC.2018.8661379
M3 - Contribución a la conferencia
AN - SCOPUS:85063898927
T3 - 2018 IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2018
BT - 2018 IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2018 IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2018
Y2 - 14 November 2018 through 16 November 2018
ER -