Windowed r-point update algorithm for Discrete Fourier Transform

Adarsh Srivastava, V. Karwal
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引用次数: 2

Abstract

In the real-time signal processing of the infinite data sequence, a portion of the sequence of length N is sampled by windowing and Discrete Fourier Transform (DFT) of that portion is computed. After computation of DFT, new input data points are shifted into the window and old data points are spilled out from the window. After shifting a new DFT has to be calculated for updated data sequence. The algorithm developed in this research is capable of updating the previously calculated DFT after shifting the data sequence over the window and reflects DFT of the updated data sequence, using less computation than directly evaluating the new transform. Previously developed algorithms were limited to a single point step between successive windows. In this research this result is extended to handle larger step sizes, i.e. the algorithm is capable to update a DFT sequence after shifting r additional data points into the window and spilling out of r old points from the window, where 1 ≤ r ≤ log2N. This Algorithm reduces the computational order by a factor of (1/ r) log2 N. The algorithm is developed for the data sequence windowed by Rectangular window and Bartlett window.
离散傅里叶变换的窗口r点更新算法
在无限数据序列的实时信号处理中,对长度为N的序列的一部分进行开窗采样,计算该部分的离散傅里叶变换(DFT)。经过DFT计算后,新的输入数据点被移到窗口中,旧的数据点被从窗口中溢出。移位后,必须为更新后的数据序列计算新的DFT。本研究开发的算法能够在数据序列在窗口上移动后更新先前计算的DFT,并反映更新后的数据序列的DFT,比直接评估新变换使用更少的计算量。以前开发的算法仅限于连续窗口之间的单点步长。在本研究中,将该结果扩展到处理更大的步长,即算法能够在将r个额外的数据点移到窗口中并从窗口中溢出r个旧点后更新DFT序列,其中1≤r≤log2N。该算法将计算顺序降低了(1/ r) log2 n倍,该算法适用于矩形窗和Bartlett窗的数据序列。
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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