Titlebook: Machine Vision and Advanced Image Processing in Remote Sensing; Proceedings of Conce Ioannis Kanellopoulos,Graeme G. Wilkinson,Theo Moo Con

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Machine Vision and Advanced Image Processing in Remote SensingProceedings of Conce

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Machine Vision and Advanced Image Processing in Remote Sensing978-3-642-60105-7

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Dimitris P. Argialasthe concepts of stochastic state space and state space modeling, based on the notionof the conditional independence of past and future flows of the relevant signals, are revealed to be fundamentally unifying ideas. The book, based on over 30 years of original research, represents a valuable contribu

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Joseph Mundy,Rupert Curwender with an engineering background will have gone through the conventional undergraduate single-input single-output linear systems course; an elementary course in control is not indispensable but may be useful for motivation. For readers from a mathematical curriculum we require only familiarity wit

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Jens Michael Carstensen,Rune Fisker,Nette Schultz,Torsten D?rgedges and Lehmann (1951) improved the sample variance by multiplying it by (n-1)/(n+1), where n is the sample size. Perlman (1972) did a more comprehensive study of this phenomenon and LaMotte (1979) proved that for a normal random model each invariant quadratic form, as an estimator of its expectati

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