Results 241 to 250 of about 17,625 (278)

Wiener reconstruction of undersampled imagery

Journal of the Optical Society of America A, 2009
We derive a Fourier-domain Wiener filter for the reconstruction of undersampled imagery. The filter differs from previous implementations in that it permits adjustment of the trade-offs between sharpness of the reconstruction, noise amplification, and aliasing artifact suppression.
Samuel T, Thurman, James R, Fienup
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Maritime Surveillance With Undersampled SAR

IEEE Geoscience and Remote Sensing Letters, 2017
According to the minimum antenna area constraint, synthetic aperture radar (SAR) systems require a low-pulse repetition frequency (PRF) to image the wide swaths in ocean surface monitoring scenarios. However, the low PRF that is lower than the Doppler bandwidth will cause azimuth ambiguities.
Yuying Wang, Zhimin Zhang 0001, Ning Li 0002, Feng Hong 0002, Huaitao Fan, Xiangyu Wang 0004   +5 more
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FIUS: Fixed partitioning undersampling method

Clinica Chimica Acta, 2021
In the medical field, data techniques for prediction and finding patterns of prevalent diseases are of increasing interest. Classification is one of the methods used to provide insight into predicting the future onset of type 2 diabetes of those at high risk of progression from pre-diabetes to diabetes.
Azam, Dekamin, M I M, Wahab, Aziz, Guergachi, Karim, Keshavjee   +3 more
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Undersampled Sine Waves

The College Mathematics Journal, 1998
(1998). Undersampled Sine Waves. The College Mathematics Journal: Vol. 29, No. 3, pp. 213-218.
Jean-Claude Derderian, Enriqueta Rodríguez-Carrington   +1 more
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An empirical comparison of repetitive undersampling techniques

2009 IEEE International Conference on Information Reuse & Integration, 2009
A common problem for data mining and machine learning practitioners is class imbalance. When examples of one class greatly outnumber examples of the other class(es), traditional machine learning algorithms can perform poorly. Random undersampling is a technique that has shown great potential for alleviating the problem of class imbalance.
Jason Van Hulse, Taghi M. Khoshgoftaar, Amri Napolitano   +2 more
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Markov processes: Estimation in the undersampled regime

2013 51st Annual Allerton Conference on Communication, Control, and Computing (Allerton), 2013
We observe a length-n sample generated by an unknown, stationary ergodic Markov process (model) over a finite alphabet A. In this paper, we do not assume any bound on the memory of the source, nor do we assume that the source is rapidly mixing. Rather we consider a class Md of all Markov sources where for all i ∈ ℕ, the mutual information between bits ...
Meysam Asadi, Ramezan Paravi Torghabeh, Narayana P. Santhanam   +2 more
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An FM demodulation algorithm with an undersampling rate

2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03)., 2004
The existing method for sampling a modulated signal is the same as that for a non-modulated message signal. Therefore, the quadrature sampling rate for a modulated signal must be larger than its bandwidth. However, a new algorithm, which can recover completely a DC-free message signal from an FM signal at a sampling rate less than its bandwidth, is ...
Yiyuan Xiong, Yi Huang 0001, Jason F. Ralph, Waleed Al-Nuaimy, Pu Sun   +4 more
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Transponder with undersampling method

2009 3rd IEEE International Symposium on Microwave, Antenna, Propagation and EMC Technologies for Wireless Communications, 2009
A transponder can encode the signal transmitted by synthetic aperture radar (SAR). The reflected signal from the encoding transponder to SAR can be imaged with the background clutters suppressed. One type of encoding transponder inverts the chirp slope of a linear frequency modulation (LFM) signal transmitted by the SAR.
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Calibrating Probability with Undersampling for Unbalanced Classification

2015 IEEE Symposium Series on Computational Intelligence, 2015
Under sampling is a popular technique for unbalanced datasets to reduce the skew in class distributions. However, it is well-known that under sampling one class modifies the priors of the training set and consequently biases the posterior probabilities of a classifier.
Andrea Dal Pozzolo, Olivier Caelen, Reid A. Johnson, Gianluca Bontempi   +3 more
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Dislaying undersampled imagery

Optical Engineering, 1994
Standard digital video displays use 640 x 480 (NTSC) or 512 x 512 (PAL) pixels to display a full screen image, while observers searching such images for small targets (or reading text) will typically operate with a screen subtense of 25 x 35 deg. Often, however, the region of interest in these images may be about 100 x 100 pixels in size, and so ...
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