Results 291 to 300 of about 828,730 (334)

Linear processing of nonuniformly sampled signals

[1991] Proceedings of the 34th Midwest Symposium on Circuits and Systems, 2002
The authors describe a novel approach, based on a coordinate transformation, that can process nonuniformly sampled signals efficiently, in the sense that the number of computations for processing the nonuniformly spaced data will be the same as in the uniform sampling case for the same number of samples in both cases. In situations where the nonuniform
Y. Feria, J. McPherson
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Perfect sampling: a review and applications to signal processing [PDF]

IEEE Transactions on Signal Processing, 2002
Markov chain Monte Carlo (MCMC) sampling methods have gained much popularity among researchers in signal processing. The Gibbs and the Metropolis-Hastings (1954, 1970) algorithms, which are the two most popular MCMC methods, have already been employed in resolving a wide variety of signal processing problems.
Yufei Huang, Petar M. Djuric, Tadesse Ghirmai   +2 more
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RF Sampling and Signal Processing

2013
As seen in Fig. 2.12 in Chap. 2, this spectrum sensing architecture uses an RF sampler followed by discrete time signal processing in the analog domain. Specifically, passive charge domain computations are utilized for signal processing followed by digitization.
Bodhisatwa Sadhu, Ramesh Harjani
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Sparse sampling of non-stationary signal for radar signal processing

2013 IEEE International Conference on Communications Workshops (ICC), 2013
Estimating the spectrogram of non-stationary signal relates to many important applications in radar signal processing. In recent years, coprime sampling and array attract attention for their potential of sparse sensing with derivative to estimate autocorrelation coefficients with all lags, which could in turn calculate the power spectrum density.
Qiong Wu, Qilian Liang
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Sampling and processing of color signals

Proceedings of 1st International Conference on Image Processing, 2002
The paper discusses the sampling of color spectra and its effect on the accuracy of derived properties such as CIE tristimulus values and color rendering indices. The effect of aliasing and common mathematical operations are discussed. >
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FFT processing of randomly sampled harmonic signals

IEEE Transactions on Signal Processing, 1992
The influence of random instabilities in the sampling instants on spectral estimation by the fast Fourier transform (FFT) of harmonic, stochastic processes is considered. The degradation due to the deviation from a uniform sampling is presented by explicit formulas.
Ilan Rusnak, A. Berkovitz
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Changeable sampling processing for chirp signals in the SAR

ICSP '98. 1998 Fourth International Conference on Signal Processing (Cat. No.98TH8344), 2002
Aimed at the chirp signal resulting from a moving target in SAR, this paper puts forward a signal processing method for changing sample ratios and gives theoretical analyses and the results of a simulation experiment. The results show that the method is very effective, practical and clearly separates a moving target, especially a slow-moving target.
Wang Shengli, Zhu Li
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Processing of signals using level-crossing sampling

2009 IEEE International Symposium on Circuits and Systems, 2009
This paper treats signals encoded using level crossing sampling. Such encoding makes possible a variable sampling rate; fast-varying parts of the signal are sampled fast, while slowly-varying parts of the signal are sampled slowly. We propose a technique for processing such signals, which results in an output with very low error.
Christos Vezyrtzis, Yannis Tsividis
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Additive random sampling for radar signal processing

2017 IEEE-APS Topical Conference on Antennas and Propagation in Wireless Communications (APWC), 2017
This paper gives an overview of challenges and opportunities in digital non-equidistant signal processing. It is pointed out that contrary to common thought non-equidistant signal processing might be of crucial interest to application, bringing important advantages for harmonics detection without having to consider Nyquist restrictions.
C. Rugheimer, F. Particke, A. Schmidt, T. Mahr   +3 more
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The Sampling Theorem of Signal Processing

2002
This overview paper treats the sampling theorem of signal analysis, and especially a variety of its applications in mathematics. These include fractional and infinite series forms of classical combinatorial identities, such as the Chu-Vandermonde convolution formula and some identities due to Hagen, the Gauss summation formula for hypergeometric ...
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