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Compressive Sampling for Signal Classification
2006 Fortieth Asilomar Conference on Signals, Systems and Computers, 2006Compressive sampling (CS), also called compressed sensing, entails making observations of an unknown signal by projecting it onto random vectors. Recent theoretical results show that if the signal is sparse (or nearly sparse) in some basis, then with high probability such observations essentially encode the salient information in the signal.
Haupt, J. +4 more
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Multichannel sampling for multiband signals
Signal Processing, 1994zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Sync signal processing for asynchronously sampled video signals
2000 IEEE International Symposium on Circuits and Systems. Emerging Technologies for the 21st Century. Proceedings (IEEE Cat No.00CH36353), 2002Digital sync signal processing for asynchronously digitized video signals is presented. A simplified matched filter for sync extraction and a linear prediction method for sync pulse filtering improves image stability significantly in comparison with a conventional phase-locked-loop (PLL) approach.
Roland Lares, Albrecht Rothermel
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Signal reconstruction from the undersampled signal samples
Optics Communications, 2006Abstract It is well-known from the celebrated Shannon sampling theorem for bandlimited signals that if the sampling rate is below the Nyquist rate, aliasing takes place and the original signal cannot be reconstructed back by simply passing the signal samples through an ideal lowpass filter. However, researchers such as Stern and Gori have shown the
Kamalesh Kumar Sharma, Shiv Dutt Joshi
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On Sampling of Bandlimited Graph Signals
2018The signal processing on graphs has been widely used in various fields, including machine learning, classification and network signal processing, in which the sampling of bandlimited graph signals plays an important role. In this paper, we discuss the sampling of bandlimited graph signals based on the theory of function spaces, which is consistent with
Mo Han +3 more
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Nonuniform Sampling for Multidimensional Signals
1987We will discuss the nonuniform samples of periodic signals first and then analyse any type of multidimensional signal. A bandlimited periodic signal is represented by a finite number of Fourier coefficients and hence can be represented by the same number of nonuniform samples per period.
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Nonuniform sampling of signals and applications
Proceedings of IEEE International Symposium on Circuits and Systems - ISCAS '94, 2002A generalization of the Whittaker-Kotel'nikov-Shannon sampling theorem to nonuniform periodic sampling is given. The novel aspect of our work is that we seek a sampling expansion in terms of time-translates of a single function. Other work on nonuniform periodic sampling has considered sampling expansions in terms of time-translates of more than one ...
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Sampling expansions for multiband signals
IEEE Transactions on Acoustics, Speech, and Signal Processing, 1985The class B I of finite energy signals bandlimited to a set I is considered where I denotes a finite union of disjoint open intervals (bands) on the real frequency axis. If such a signal is sampled uniformly (constant intersample spacing T), it is shown that the following five propositions are equivalent.
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Learning to Sample for Sparse Signals
ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2022Satish Mulleti +2 more
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Delay sampling theorem: A criterion for the recovery of multitone signal
Mechanical Systems and Signal Processing, 2023Jiahui Cao, Zhibo Yang, Ruo-Bin Sun
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