On the approximation of nonbandlimited signals by nonuniform sampling series

P. Ferreira
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引用次数: 7

Abstract

The classical WKS sampling theorem is a central result in signal processing, but it applies to band-limited signals only. For many purposes, this class of signals is too narrow. For example, the signals that occur in practice are invariably of finite duration, or time-limited, and often have discontinuities. Clearly, such signals cannot be band-limited. We consider the problem of approximating such signals, or other signals not necessarily band-limited, using sampling series. We do not assume that the sampling instants are regularly distributed, in order to account for errors due to jitter. To the best of our knowledge, the problem of obtaining nonuniform sampling approximations for signals not necessarily band-limited, despite its practical interest, has not been addressed in the literature. In this work we introduce a method that leads to sampling approximations with the required properties. It is shown that the sampling sums considered are capable of approximating a wide class of signals, with arbitrarily small L2 and L∞ errors.
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非均匀采样序列对非带限信号的逼近
经典的WKS采样定理是信号处理中的一个核心结果,但它只适用于带限信号。对于许多用途来说,这类信号太窄了。例如,实际中出现的信号总是有限持续时间或有时间限制的,并且常常具有不连续性。显然,这样的信号不可能是带限制的。我们考虑使用采样序列逼近此类信号或其他不一定带限的信号的问题。为了考虑抖动引起的误差,我们不假设采样瞬间是规则分布的。据我们所知,获取信号的非均匀采样逼近的问题不一定是带限制的,尽管它的实际利益,还没有在文献中解决。在这项工作中,我们介绍了一种方法,导致采样近似所需的性质。结果表明,所考虑的采样和能够近似广泛的信号,具有任意小的L2和L∞误差。
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PDF Not Yet Available In IEEE Xplore Parameter estimation of exponentially damped sinusoids using second order statistics A multivariable Steiglitz-McBride method On the approximation of nonbandlimited signals by nonuniform sampling series Model reduction by Kautz filters
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