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The Fast Fourier Transform for Experimentalists Part Ⅲ: Classical Spectral Analysis

机译:实验者的快速傅里叶变换第三部分:经典光谱分析

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摘要

Each article in this continuing series on the fast fourier transform (FFT) is designed to illuminate new features of the wide-ranging applicability of this transform. This segment deals with some aspects of the spectrum estimation problem. Before we begin, here's a short refresher about two elements we introduced previously, windowing and convolution. As we noted in those installments, a convolution is an integral that expresses the amount of overlap of one function as it is shifted over another. The result is a blending of the two functions?
机译:这个连续系列中有关快速傅立叶变换(FFT)的每篇文章都旨在阐明这种变换的广泛适用性的新特征。此部分处理频谱估计问题的某些方面。在开始之前,这里简要介绍一下我们先前介绍的两个元素,即窗口化和卷积。正如我们在那些部分中所提到的,卷积是一个整数,表示一个函数在移至另一个函数时的重叠量。结果是两个功能的融合?

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