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Statistical Comparison of CLEAN and MEM

Published online by Cambridge University Press:  12 April 2016

M. Ishiguro
Affiliation:
The Institute of Statistical Mathematics, 6-7 Minami-Azabu 4-chome, Minato-ku, Tokyo 106 Japan
M. Ishiguro
Affiliation:
Nobeyama Radio Observatory, National Astronomical Observatory, Nobeyama, Minamimaki, Minamisaku, Nagano 384-13 Japan
K.-I. Morita
Affiliation:
Nobeyama Radio Observatory, National Astronomical Observatory, Nobeyama, Minamimaki, Minamisaku, Nagano 384-13 Japan
Y. Murata
Affiliation:
The Institute of Space and Astronomical Science, 1-1 Yoshinodai 3-chome, Sagamihara 229 Japan

Extract

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Assume that a set of visibility data

{(uj, vj, zj)| j = 1, 2,...,N}

is given where visibility zj observed at time j can be expressed in terms of “true visibility” defined by the brightness distribution T(x,y) and observation noise εj:

where{(uj, vj)} is a given set of points in the u-v plane. It is assumed that u-v plane is gridded with the interval Δ. The dirty map obtained by

is a crude estimate of the true brightness distribution. CLEAN and MEM are two typical methods to get better estimates.

Type
2. Technical Innovations
Copyright
Copyright © Astronomical Society of the Pacific 1994

References

Akaiké, H. 1973, Information theory and an extension of the maximum likelihood principle, 2nd International Symposium on Information Theory (Petrov, B. N. and Csaki, F. eds.), Akadémiai Kiadó, Budapest, pp.267281. (Reproduced in Breakthroughs in Statistics, volume 1, Kotz, S. and Johnson, N. L., eds., Springer Verlag, New York, (1992).)Google Scholar
(Ishiguro, M.)2 and Morita, K.-I. 1991, Application of an Estimator-Free Information Criterion( WIC) to Aperture Synthsis Imaging, in Radio Interferometry: Theory, Techniques and Applications (Cornwell, T.J. and Perley, R.A. eds.), IAU Coll. 131, ASP Conference Series, 19, 243.Google Scholar