Results 271 to 280 of about 261,559 (305)

Sampling Theory in Signal and Image Processing

, 2011
Besides the proceedings, participants were invited to prepare an extended version of their SAMPTA contribution for a special issue of STSIP. Ten papers were accepted, covering a wide range of aspects of sampling theory (classical sampling, frame theory, wavelets, multi-resolution, operator approximation) and applications (impulse radio ultra-wide band,
Fesquet, Laurent, Torrésani, B.
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Compressed Signal Processing on Nyquist-Sampled Signals

IEEE Transactions on Computers, 2016
Pattern-recognition algorithms from the domain of machine learning play a prominent role in embedded sensing systems, in order to derive inferences from sensor data. Very often, such systems face severe energy constraints. The focus of this work is to mitigate the computational energy by exploiting a form of compression which preserves a similarity ...
Jie Lu, Naveen Verma, Niraj K. Jha
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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), 2002
Digital 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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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 0006, Qilian Liang
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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 P. Tsividis
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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.
Aharon Berkovitz, Ilan Rusnak
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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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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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The processing of periodically sampled multidimensional signals

IEEE Transactions on Acoustics, Speech, and Signal Processing, 1983
This paper discusses algorithms for processing multidimensional signals which are sampled on regular, but nonrectangular sampling lattices. Such sampling lattices are dictated by some applications and may be chosen for others because of their resulting symmetric responses or computational efficiencies.
Mersereau, Russell M., Speake, Theresa C.   +1 more
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Processing schemes for sampled multi-dimensional signals

ICASSP '82. IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005
In addition to filtering also other operations like insertion of zeros etc. can be employed for the processing of multi-dimensional data arrays. A list of these operations and some examples will be presented. The mathematical description will be given by means of appropriate impulse fields and their Fourier transforms rather than by means of the z ...
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