Topic
Coherent sampling
About: Coherent sampling is a research topic. Over the lifetime, 1115 publications have been published within this topic receiving 26593 citations.
Papers published on a yearly basis
1 / 2
Papers
TL;DR: The theory of compressive sampling, also known as compressed sensing or CS, is surveyed, a novel sensing/sampling paradigm that goes against the common wisdom in data acquisition.
Abstract: Conventional approaches to sampling signals or images follow Shannon's theorem: the sampling rate must be at least twice the maximum frequency present in the signal (Nyquist rate). In the field of data conversion, standard analog-to-digital converter (ADC) technology implements the usual quantized Shannon representation - the signal is uniformly sampled at or above the Nyquist rate. This article surveys the theory of compressive sampling, also known as compressed sensing or CS, a novel sensing/sampling paradigm that goes against the common wisdom in data acquisition. CS theory asserts that one can recover certain signals and images from far fewer samples or measurements than traditional methods use.
11,211 citations
10 Dec 2002
TL;DR: In this paper, it is shown that Lebesgue sampling gives better performance for some simple systems than traditional Riemann sampling, which is an analog of integration theory and is called event-based sampling.
Abstract: The normal approach to digital control is to sample periodically in time. Using an analog of integration theory we can call this Riemann sampling. Lebesgue sampling or event based sampling is an alternative to Riemann sampling. It means that signals are sampled only when measurements pass certain limits. In this paper it is shown that Lebesgue sampling gives better performance for some simple systems.
1,051 citations
TL;DR: This paper investigates some simple first order systems with event based sampling and compares achieved closed loop variance and sampling rate with results from periodic sampling and shows that event based sampled gives better performance than periodic sampling.
847 citations
TL;DR: This paper observes that one of the standard interpolation or "gridding" schemes, based on Gaussians, can be accelerated by a significant factor without precomputation and storage of the interpolation weights, of particular value in two- and three- dimensional settings.
Abstract: The nonequispaced Fourier transform arises in a variety of application areas, from medical imaging to radio astronomy to the numerical solution of partial differential equations. In a typical problem, one is given an irregular sampling of N data in the frequency domain and one is interested in reconstructing the corresponding function in the physical domain. When the sampling is uniform, the fast Fourier transform (FFT) allows this calculation to be computed in O(N log N ) operations rather than O(N 2 ) operations. Unfortunately, when the sampling is nonuniform, the FFT does not apply. Over the last few years, a number of algorithms have been developed to overcome this limitation and are often referred to as nonuniform FFTs (NUFFTs). These rely on a mixture of interpolation and the judicious use of the FFT on an oversampled grid (A. Dutt and V. Rokhlin, SIAM J. Sci. Comput., 14 (1993), pp. 1368-1383). In this paper, we observe that one of the standard interpolation or "gridding" schemes, based on Gaussians, can be accelerated by a significant factor without precomputation and storage of the interpolation weights. This is of particular value in two- and three- dimensional settings, saving either 10 d N in storage in d dimensions or a factor of about 5-10 in CPUtime (independent of dimension).
833 citations
TL;DR: In this article, it was shown that a band-limited function f(t) is uniquely determined in terms of the samples g_k(nT) of the responses of m linear systems with input f (t), sampled at 1/m the Nyquist rate.
Abstract: It is shown that a band-limited function f(t) is uniquely determined in terms of the samples g_k(nT) of the responses g_k(t) of m linear systems with input f(t) , sampled at 1/m the Nyquist rate. Various known extensions of the sampling theorem follow as special cases of the resulting generalized sampling expansion of f(t) .
733 citations
Related Topics (5)
Performance Metrics
| Year | Papers |
|---|---|
| 2024 | 1 |
| 2023 | 3 |
| 2022 | 16 |
| 2021 | 6 |
| 2020 | 5 |
| 2019 | 7 |