Genetic Algorithm-Based Adaptive Active Noise Control Without Secondary Path Identification-Reference-Cited by-同舟云学术

Genetic Algorithm-Based Adaptive Active Noise Control Without Secondary Path Identification

Published:2023 Issue: Volume:72 Page:1-9
ISSN:0018-9456
Container-title:IEEE Transactions on Instrumentation and Measurement
language:
Short-container-title:IEEE Trans. Instrum. Meas.

Author:

Zhou Yang¹^ORCID,Zhao Haiquan¹^ORCID,Liu Dongxu¹^ORCID

Affiliation:

1. Key Laboratory of Magnetic Suspension Technology and Maglev Vehicle, Ministry of Education, and the School of Electrical Engineering, Southwest Jiaotong University, Chengdu, China

Funder

National Natural Science Foundation of China

Chengdu Guojia Electrical Engineering Company Ltd.

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

http://xplorestaging.ieee.org/ielx7/19/10012124/10233064.pdf?arnumber=10233064

Reference43 articles.

1. A secondary path modeling technique for active noise control systems

2. Impedance Measurements Using Genetic Algorithms and Multiharmonic Signals

3. Use of random noise for on‐line transducer modeling in an adaptive active attenuation system

4. Accuracy and Performance Evaluation in the Genetic Optimization of Nonlinear Systems for Active Noise Control

5. Deep ANC: A deep learning approach to active noise control

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