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Fast Least-Squares Solution for Sinusoidal, Harmonic and Quasi-Harmonic Models

机译:用于正弦,谐波和准谐波模型的快度最小二乘解

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摘要

Sinusoidal model and its variants are commonly used in speech processing. In the literature, there are various methods for the estimation of the unknown parameters of sinusoidal model such as Fourier transform based on FFT algorithm and Least Squares (LS) method. Least Squares method is more accurate and actually optimum for Gaussian noise, thus, more appropriate for high-quality signal processing, however, it is slower compared with FFT-based algorithms. In this paper, we study the source of computational load of LS solution and propose various computational improvements. We show that the complexity of LS solution as well the execution time are highly improved.
机译:正弦模型及其变体通常用于语音处理。在文献中,存在各种方法来估计基于FFT算法和最小二乘(LS)方法的傅里叶变换的正弦模型未知参数。最小二乘方法更准确,更适合高斯噪声,因此更适合高质量的信号处理,然而,与基于FFT的算法相比,它比较慢。在本文中,我们研究了LS解决方案的计算负荷来源,提出了各种计算改进。我们表明LS解决方案以及执行时间的复杂性高度改善。

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