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Titlebook: Statistical Challenges in Modern Astronomy; Eric D. Feigelson,G. Jogesh Babu Book 1992 Springer-Verlag New York, Inc. 1992 Parameter.Power

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书目名称Statistical Challenges in Modern Astronomy
编辑Eric D. Feigelson,G. Jogesh Babu
视频video
图书封面Titlebook: Statistical Challenges in Modern Astronomy;  Eric D. Feigelson,G. Jogesh Babu Book 1992 Springer-Verlag New York, Inc. 1992 Parameter.Power
描述Modern astronomy has been characterized by an enormous growth in data acquisition - from new technologies in telescopes, detectors, and computation. One can now compile catalogs of tens or hundreds of millions of stars or galaxies and databases from satellite-based observations are reaching terabit proportions. This wealth of data gives rise to statistical challenges not previously encountered in astronomy. This book is the result of a workshop held at Pennsylvania State University in August 1991 that brought together leading astronomers and statisticians to consider statistical challenges encountered in modern astronomical research. The chapters have all been thoroughly revised in the light of the discussions at the conference, and some of the lively discussion is recorded here as well.
出版日期Book 1992
关键词Parameter; Power; Redshift; astronomy; astrophysics; cosmology; databases; galaxies; galaxy; growth; image ana
版次1
doihttps://doi.org/10.1007/978-1-4613-9290-3
isbn_softcover978-1-4613-9292-7
isbn_ebook978-1-4613-9290-3
copyrightSpringer-Verlag New York, Inc. 1992
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Eric D. Feigelson,G. Jogesh Baburete Handlungsanleitungen für die klinische NotfallsituationParavasation von Zytostatika kann zu schwerwiegenden Zwischen- und Notfällen bei der Tumortherapie führen. Das überarbeitete Kompendium hilft die jeweilige Situation rasch und sicher einzuschätzen. Im allgemeinen Teil werden umfassend die T
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Eric D. Feigelson,G. Jogesh Babuemembering, and reasoning in real time, even approaching the brain‘s speed and power — IF we knew how to build them. This paper proposes and explores a promising but largely ignored information-flow approach..For maximum speed and efficiency, massively parallel networks should be structured so that
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Peter Colesemembering, and reasoning in real time, even approaching the brain‘s speed and power — IF we knew how to build them. This paper proposes and explores a promising but largely ignored information-flow approach..For maximum speed and efficiency, massively parallel networks should be structured so that
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Eric D. Feigelson,G. Jogesh Babu and many-body-models. The mathematical approximative methods used are numerical grid methods, molecular dynamics, Monte Carlo methods etc. The more complicate the considered phenomenon and the more refined the model is, the higher is the demand for computational power and storage capacity. Future h
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