Results 1 to 10 of about 9,812 (256)

On the efficiency of techniques for the reduction of impulsive noise in astronomical images [PDF]

Monthly Notices of the Royal Astronomical Society, 2016
The impulsive noise in astronomical images originates from various sources. It develops as a result of thermal generation in pixels, collision of cosmic rays with image sensor or may be induced by high readout voltage in Electron Multiplying CCD (EMCCD).
Adam Popowicz, Tomasz Blachowicz, Blachowicz T   +2 more
exaly   +4 more sources

Some Astronomical Applications of Cross-Correlation Techniques. [PDF]

The Astrophysical Journal, 1965
Cross-correlation techniques have been used for many years to increase the signal-to-noise ratio of a wide variety of analogue and digital data. A large literature describing these methods exists, and many clever applications have been developed (see Fellgett 1953, and esp. Woodward 1955, for a basic mathematical development and applications).
Westphal, J. A.
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Astronomical site selection for Turkey using GIS techniques [PDF]

Experimental Astronomy, 2015
A site selection of potential observatory locations in Turkey have been carried out by using Multi-Criteria Decision Analysis (MCDA) coupled with Geographical Information Systems (GIS) and satellite imagery which in turn reduced cost and time and increased the accuracy of the final outcome. The layers of cloud cover, digital elevation model, artificial
Aksaker, N., Yerli, S. K., Erdogan, M. A., Erdi, E., Kaba, K., Ak, T., Aslan, Z., Bakis, V., Demircan, O., Evren, S., Keskin, V., Kucuk, I., Ozdemir, T., Ozisik, T., Selam, S. O.   +14 more
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Parametric High Resolution Techniques for Radio Astronomical Imaging [PDF]

IEEE Journal of Selected Topics in Signal Processing, 2008
The increased sensitivity of future radio telescopes will result in requirements for higher dynamic range within the image as well as better resolution and immunity to interference. In this paper we propose a new matrix formulation of the imaging equation in the cases of non co-planar arrays and polarimetric measurements. Then we improve our parametric
Chen Ben-David, Amir Leshem
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Analyzing astronomical data with machine learning techniques

Astronomical and Astrophysical Transactions, 2022
Classification is a popular task in the field of machine learning (ML) and artificial intelligence (AI), and it happens when outputs are categorical variables. There are a wide variety of models that attempt to draw some conclusions from observed values, so classification algorithms predict categorical class labels for use in classifying new data ...
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Radio Interference and Ejecting Techniques at Beijing Astronomical Observatory [PDF]

Symposium - International Astronomical Union, 2001
In this paper, we first describe the situation of radio interference at the Miyun station in Beijing Astronomical Observatory, and then new developments in both hardware and software techniques of interference rejection for the Miyun Synthesis Radio Telescope (MSRT) are described.
X. Zhang, T. Piao, B. Peng, X. Wang
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The Influence of Acquisition Techniques on the Compilation of Astronomical Data [PDF]

International Astronomical Union Colloquium, 1977
With the increasing use of electronic rather than photographic data collection, and on-line minicomputers at the telescope, two factors will necessitate a reconsideration of the way in which data are stored at the telescope.1) Many of the electronic data collecting methods produce data in a final or semifinal (digital) form and usually with a large ...
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Astronomical techniques in intensive care [PDF]

Astronomy & Geophysics, 2015
L. K. Harra, T. Pollard, D. Williams, K. Fong   +3 more
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Recursive Anchoring Techniques in Astronomical Data Analysis

Journal of Research in Science and Engineering
The conventional approach to astronomical research assumes that large - scale observational data is necessary to define cosmic structures. This paper proposes a recursive anchoring method where a fraction of the dataset, when correctly defined within a recursive framework, can reconstruct the same “center of existence” as a full dataset.
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Deep Learning Techniques for Astronomical Object Classification

, 2022
As there are an infinite number of deep space objects, it is crucial to differentiate those space objects such as stars, galaxies, or quasars in recent or upcoming deep astronomical surveys. This task becomes very difficult because of the tedious procedure for separation between edgy and expanded sources, which makes this classification problem a ...
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