An investigation on the plant modeling filter's parameters for active noise control system

Jinjun Wang; Kean Chen; Guoyue Chen; Kenji Muto

doi:10.1093/ietfec/e89-a.6.1847

An investigation on the plant modeling filter's parameters for active noise control system

Jinjun Wang, Kean Chen, Guoyue Chen, Kenji Muto

Research output: Contribution to journal › Article › peer-review

2 Citations (Scopus)

Abstract

Usually an FIR filter is used to model the physical paths in an active noise control system. However, the order of the filter to be modeled is a key factor for determining the computational load for the adaptive algorithms associated with active noise control (ANC), particularly for multi-channel algorithms. In this letter, the relationships among the filter's order, the plant modeling error and the location of poles for the transfer functions of the physical paths in an ANC system are theoretically examined and numerical examples are given to verify the theoretical results.

Original language	English
Pages (from-to)	1847-1851
Number of pages	5
Journal	IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
Volume	E89-A
Issue number	6
DOIs	https://doi.org/10.1093/ietfec/e89-a.6.1847
Publication status	Published - 2006 Jun
Externally published	Yes

Keywords

Active noise control
FIR filter
IIR filter
Path modeling

ASJC Scopus subject areas

Signal Processing
Computer Graphics and Computer-Aided Design
Electrical and Electronic Engineering
Applied Mathematics

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10.1093/ietfec/e89-a.6.1847

Cite this

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abstract = "Usually an FIR filter is used to model the physical paths in an active noise control system. However, the order of the filter to be modeled is a key factor for determining the computational load for the adaptive algorithms associated with active noise control (ANC), particularly for multi-channel algorithms. In this letter, the relationships among the filter's order, the plant modeling error and the location of poles for the transfer functions of the physical paths in an ANC system are theoretically examined and numerical examples are given to verify the theoretical results.",

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AU - Chen, Kean

AU - Chen, Guoyue

AU - Muto, Kenji

PY - 2006/6

Y1 - 2006/6

N2 - Usually an FIR filter is used to model the physical paths in an active noise control system. However, the order of the filter to be modeled is a key factor for determining the computational load for the adaptive algorithms associated with active noise control (ANC), particularly for multi-channel algorithms. In this letter, the relationships among the filter's order, the plant modeling error and the location of poles for the transfer functions of the physical paths in an ANC system are theoretically examined and numerical examples are given to verify the theoretical results.

AB - Usually an FIR filter is used to model the physical paths in an active noise control system. However, the order of the filter to be modeled is a key factor for determining the computational load for the adaptive algorithms associated with active noise control (ANC), particularly for multi-channel algorithms. In this letter, the relationships among the filter's order, the plant modeling error and the location of poles for the transfer functions of the physical paths in an ANC system are theoretically examined and numerical examples are given to verify the theoretical results.

KW - Active noise control

KW - FIR filter

KW - IIR filter

KW - Path modeling

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An investigation on the plant modeling filter's parameters for active noise control system

Abstract

Keywords

ASJC Scopus subject areas

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