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Reduced-complexity modeling of high-order nonlinear audio systems using swept-sine and principal component analysis

机译:使用扫频正弦和主成分分析的高阶非线性音频系统的降低复杂度建模

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Modeling high-order nonlinear systems is an important issue in audio signal processing. It may be employed in real-time emulation of analog nonlinear systems, such as guitar distortion and amplifiers or other vintage electronic audio systems. This paper proposes a new method for obtaining an economical black-box model of nonlinear systems using the swept-sine technique, which extracts the harmonic distortion at each frequency by separating them in time. In the proposed model the swept-sine technique is used to obtain the time-frequency representation of a nonlinear system, and the principal component analysis is used to reduce the complexity of the model. It is shown that the proposed method reduces the computational cost by 66% when compared to traditional swept-sine models.
机译:对高阶非线性系统建模是音频信号处理中的重要问题。它可以用于模拟非线性系统的实时仿真,例如吉他失真和放大器或其他老式电子音频系统。本文提出了一种使用后扫正弦技术获得经济的非线性系统黑匣子模型的新方法,该方法通过及时分离每个频率提取谐波失真。在提出的模型中,使用正弦扫频技术获得非线性系统的时频表示,并使用主成分分析来降低模型的复杂性。结果表明,与传统的正弦扫频模型相比,该方法将计算成本降低了66%。

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