RLS algorithm in active noise control

D. Bismor

RLS algorithm in active noise control

D. Bismor

Katedra Pomiarów i Systemów Sterowania (RAU/RAU2)

Wyniki badań: Wkład do czasopisma › Artykuł › recenzja

Abstrakt

Although the least mean squares (LMS) method is the most popular among adaptation algorithms used for active noise control, it has some disadvantages, such as steady-state error and slow convergence for some signals. This article presents results of active noise control in an acoustic duct obtained with a recursive least squares algorithm. Results are compared to those obtained with an LMS algorithm.

Język oryginału	angielski
Strony (od–do)	58-59
Liczba stron	2
Czasopismo	Shock and Vibration Digest
Tom	32
Numer wydania	1
Status publikacji	Opublikowano - sty 2000

Obszary tematyczne ASJC Scopus

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Cytowanie

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title = "RLS algorithm in active noise control",

abstract = "Although the least mean squares (LMS) method is the most popular among adaptation algorithms used for active noise control, it has some disadvantages, such as steady-state error and slow convergence for some signals. This article presents results of active noise control in an acoustic duct obtained with a recursive least squares algorithm. Results are compared to those obtained with an LMS algorithm.",

author = "D. Bismor",

year = "2000",

month = jan,

language = "English",

volume = "32",

pages = "58--59",

journal = "Shock and Vibration Digest",

issn = "0583-1024",

publisher = "SAGE Publications Inc.",

number = "1",

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TY - JOUR

T1 - RLS algorithm in active noise control

AU - Bismor, D.

PY - 2000/1

Y1 - 2000/1

N2 - Although the least mean squares (LMS) method is the most popular among adaptation algorithms used for active noise control, it has some disadvantages, such as steady-state error and slow convergence for some signals. This article presents results of active noise control in an acoustic duct obtained with a recursive least squares algorithm. Results are compared to those obtained with an LMS algorithm.

AB - Although the least mean squares (LMS) method is the most popular among adaptation algorithms used for active noise control, it has some disadvantages, such as steady-state error and slow convergence for some signals. This article presents results of active noise control in an acoustic duct obtained with a recursive least squares algorithm. Results are compared to those obtained with an LMS algorithm.

UR - https://www.scopus.com/pages/publications/0033907598

M3 - Article

AN - SCOPUS:0033907598

SN - 0583-1024

VL - 32

SP - 58

EP - 59

JO - Shock and Vibration Digest

JF - Shock and Vibration Digest

IS - 1

ER -

RLS algorithm in active noise control

Abstrakt

Obszary tematyczne ASJC Scopus

Inne pliki i linki

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Cytowanie