Antiderivative antialiasing, lagrange interpolation and spectral flatness

S. Bilbao, Fabian Esqueda, V. Välimäki
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引用次数: 6

Abstract

Aliasing is major problem in any audio signal processing chain involving nonlinearity. The usual approach to antialiasing involves operation at an oversampled rate—usually 4 to 8 times an audio sample rate. Recently, a new approach to antialiasing in the case of memoryless nonlinearities has been proposed, which relies on operations over the antiderivative of the nonlinear function, and which allows for antialiasing at audio or near-audio rates, and without regard to the particular form of the nonlinearity (i.e., polynomial, or hard clipping). Such techniques may be deduced through an application of Lagrange interpolation over unequally-spaced values, and, furthermore, may be constrained to behave as spectrally transparent “throughs” for nonlinearities which reduce to linear at low signal amplitudes. Numerical results are presented.
不定导数抗混叠,拉格朗日插值和光谱平坦
混叠是任何涉及非线性的音频信号处理链中的主要问题。通常的抗混叠方法包括以过采样率操作——通常是音频采样率的4到8倍。最近,在无记忆非线性的情况下,已经提出了一种新的抗混叠方法,它依赖于非线性函数的不定积分运算,并允许在音频或近音频速率下进行抗混叠,而不考虑非线性的特定形式(即多项式或硬裁剪)。这样的技术可以通过拉格朗日插值在不等间隔值上的应用来推导,而且,可能被限制为在低信号幅度下降低为线性的非线性的频谱透明“通过”。给出了数值结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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