Results 1 to 10 of about 1,946,431 (327)
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Journal of Chemometrics, 2005
AbstractIn many applications it is expected from theory that a signal should be non‐negative and unimodal, that is, show only one peak. If the data are noisy, standard smoothing algorithms will not always give the desired result: peaks may be rounded and negative lobes may occur in the tails.
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AbstractIn many applications it is expected from theory that a signal should be non‐negative and unimodal, that is, show only one peak. If the data are noisy, standard smoothing algorithms will not always give the desired result: peaks may be rounded and negative lobes may occur in the tails.
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Smoothing and differentiation of data by simplified least square procedure.
Analytical Chemistry, 1964Jean. Steinier +2 more
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Management Science, 1961
The production planning model of Modigliani and Hohn and the smoothing model of Hoffman and Jacobs are combined. The most interesting result is that the horizon planning properties of the individual models are retained in the combined model. Methods are also given for the computation of optimal production schedules for certain kinds of requirements ...
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The production planning model of Modigliani and Hohn and the smoothing model of Hoffman and Jacobs are combined. The most interesting result is that the horizon planning properties of the individual models are retained in the combined model. Methods are also given for the computation of optimal production schedules for certain kinds of requirements ...
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Journal of Microscopy, 2002
SummaryA modification of the general fractionator sampling technique called the smooth fractionator is presented. It may be used in almost every situation in which sampling is performed from distinct items that are uniquely defined, often they are physically separated items or clusters like pieces, blocks, slabs, sections, etc.
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SummaryA modification of the general fractionator sampling technique called the smooth fractionator is presented. It may be used in almost every situation in which sampling is performed from distinct items that are uniquely defined, often they are physically separated items or clusters like pieces, blocks, slabs, sections, etc.
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Smoothing noisy data with spline functions
, 1978Peter Craven, G. Wahba
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A Generalized Framework for Edge-Preserving and Structure-Preserving Image Smoothing
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022Wei Liu, Yingjie Lei, Xiaolin Huang
exaly
Bayesian Filtering and Smoothing
Institute of Mathematical Statistics textbooks, 2013Simo Särkkä
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Smoothing reference centile curves: the LMS method and penalized likelihood.
Statistics in Medicine, 1992T. Cole, P. Green
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How Does Intentional Earnings Smoothing Vary With Managerial Ability?
, 2020Peter R. Demerjian +2 more
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