Leaky Partial Update LMS Algorithms in Application to Structural Active Noise Control
1Department of Measurements and Control Systems, Silesian University of Technology, ul. Akademicka 16, 44-100 Gliwice, Poland.
Sensors (Basel, Switzerland)
|February 11, 2023
Summary
Partial update adaptive algorithms offer significant computational savings for structural active noise control systems. Leaky versions of these algorithms demonstrate high performance in simulations, making them suitable for demanding applications.
Area of Science:
- Signal Processing
- Acoustics
- Control Systems
Background:
- Adaptive signal processing is crucial in fields like telecommunications and noise control.
- Partial update adaptive algorithms are gaining attention for their efficiency.
- Structural active noise control (ANC) systems offer global noise reduction but are computationally intensive.
Purpose of the Study:
- To investigate the application of partial updates (PUs) in demanding structural active noise control (ANC) systems.
- To explore modifications for applying PUs in ANC and quantify computational power savings.
- To introduce leaky versions of PU LMS algorithms for structural ANC.
Main Methods:
- Modified partial update least mean squares (LMS) algorithms were developed for structural ANC.
- Computational power requirements were analyzed for PU application in multichannel ANC.
- Simulations based on real laboratory setups were conducted.
Main Results:
- Partial updates significantly reduce computational requirements in structural ANC systems.
- Leaky PU LMS algorithms were successfully introduced and applied.
- Simulations confirmed the high performance of the proposed algorithms.
Conclusions:
- Partial update adaptive algorithms are effective in reducing the computational load of structural ANC systems.
- The proposed leaky PU LMS algorithms are well-suited for high-performance structural ANC.
- The findings support the practical application of PUs in advanced noise control solutions.
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