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Theoretical and numerical aspects of an SVD-based method for band-limiting finite-extent sequences

机译:基于SVD的带限有限范围序列方法的理论和数值方面

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The authors present an SVD-based method for band-limiting over-sampled discrete-time finite-extent sequences. For this purpose, they show that finite-extent band limitation is best defined in terms of the discrete prolate spheroidal sequences rather than complex exponentials. Their method has maximum energy concentration as defined in the paper, its dimension agrees asymptotically with Slepian's (1978) dimension result, and the method specializes correctly to the discrete-time Fourier transform as the sample size tends to infinity. They propose an efficient computational method, based on the Lanczos algorithm, for computing only the necessary singular vectors. The SVD is signal-independent, only needs to be done once and can be precomputed. The SVD-based band limitation itself is not necessarily much slower than the fast Fourier transform for sample sizes on the order of 4096.
机译:作者提出了一种基于SVD的方法,用于对过采样的离散时间有限范围序列进行带宽限制。为此,他们表明,最好用离散的扁长球体序列而不是复指数来定义有限范围的频带限制。他们的方法具有本文定义的最大能量集中度,其维数与Slepian(1978)的维数渐近一致,并且该方法正确地专门用于离散时间傅立叶变换,因为样本量趋于无穷大。他们提出了一种基于Lanczos算法的有效计算方法,该方法只计算必要的奇异矢量。 SVD与信号无关,只需执行一次即可进行预先计算。对于4096级左右的样本量,基于SVD的频带限制本身不一定比快速傅里叶变换慢很多。

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