准牛顿同时扰动随机近似算法用于宽带主动噪声控制 (L)
Ruquan Sun1, Tianyou Li1, Xiaofeng Zeng1
1Key Laboratory of Modern Acoustics, Institute of Acoustics, Nanjing University, Nanjing 210093, China.
本研究介绍了一种主动噪声控制 (ANC) 算法,该算法将同时扰动随机近似 (SPSA) 与准牛顿方法相结合,以更好地减少宽带噪声. 新的方法提供了更快的融合和减少在噪音环境中的错误.
科学领域:
- 声学和信号处理
- 控制系统工程 控制系统工程
- 计算数学 计算数学 计算数学
背景情况:
- 积极噪音控制 (ANC) 对于减少不必要的声音至关重要.
- 现有的方法,如SPSA,在有效的宽带降噪方面面临挑战.
- 梯度估计和过器更新是ANC性能的关键.
研究的目的:
- 开发一个先进的ANC算法,以提高宽带噪声降低.
- 将同步扰动随机近似 (SPSA) 与准牛顿方法整合起来.
- 为了提高合速度并减少ANC系统中的稳定状态误差.
主要方法:
- 提出了一个集成SPSA和准牛顿方法的ANC算法.
- 开发了高效的梯度估计和控制波器和反向赫森矩阵的同时更新.
- 使用车载噪声数据验证了算法.
主要成果:
- 与现有的SPSA方法相比,拟议的ANC算法显示了更快的趋同.
- 实现了较低的平稳状态平均平方误差.
- 在现实世界的车载噪声场景中,在计算开销最小的情况下展示了有效性.
结论:
- 集成的SPSA和准牛顿ANC算法显著提高宽带噪声降低.
- 该方法比传统的SPSA提供了改进的性能指标 (融合,错误).
- 这种方法为实际ANC应用提供了一个计算效率高的解决方案.
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