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Sparse Interpolation, the FFT Algorithm and FIR Filters

机译:稀疏插值,FFT算法和FIR滤波器

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In signal processing, the Fourier transform is a popular method to analyze the frequency content of a signal, as it decomposes the signal into a linear combination of complex exponentials with integer frequencies. A fast algorithm to compute the Fourier transform is based on a binary divide and conquer strategy. In computer algebra, sparse interpolation is well-known and closely related to Prony's method of exponential fitting, which dates back to 1795. In this paper we develop a divide and conquer algorithm for sparse interpolation and show how it is a generalization of the FFT algorithm. In addition, when considering an analog as opposed to a discrete version of our divide and conquer algorithm, we can establish a connection with digital filter theory.
机译:在信号处理中,傅立叶变换是一种分析信号频率内容的流行方法,因为它将信号分解为具有整数频率的复指数线性组合。一种快速的傅立叶变换算法是基于二进制的分治策略。在计算机代数中,稀疏插值是众所周知的并且与Prony的指数拟合方法(可追溯到1795年)密切相关。在本文中,我们开发了一种稀疏插值的分而治之算法,并展示了它是FFT算法的推广。另外,当考虑模拟而不是分而治之算法的离散版本时,我们可以与数字滤波器理论建立联系。

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