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040   $aDip.to Fisica$bita
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100 1 $aBracewell, Ronald N.$0462093
245 14$aThe Fourier transforms and its applications /$c[by] Ron Bracewell
260   $aNew York :$bMcGraw-Hill Book Co.,$cc1965
300   $aviii, 381 p. :$bill. ;$c23 cm.
500   $aBibliography : p. 23.
650  4$aFourier transformations
650  4$aHarmonic analysis
650  4$aTransformations (Mathematics)
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996   $aFourier transforms and its applications$9187937
997   $aUNISALENTO
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100   $a20170816d2017      u|         0
101 0 $aeng
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181   $2rdacontent
182   $2rdamedia
183   $2rdacarrier
200 10$aAlgorithms and Programs of Dynamic Mixture Estimation $eUnified Approach to Different Types of Components /$fby Ivan Nagy, Evgenia Suzdaleva
205   $a1st ed. 2017.
210  1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2017.
215   $a1 online resource (113 pages) $cillustrations, tables
225 1 $aSpringerBriefs in Statistics,$x2191-5458
311 08$a3-319-64670-2 
320   $aIncludes bibliographical references.
327   $aIntroduction -- Basic Models -- Statistical Analysis of Dynamic Mixtures -- Dynamic Mixture Estimation -- Program Codes -- Experiments -- Appendices.
330   $aThis book provides a general theoretical background for constructing the recursive Bayesian estimation algorithms for mixture models. It collects the recursive algorithms for estimating dynamic mixtures of various distributions and brings them in the unified form, providing a scheme for constructing the estimation algorithm for a mixture of components modeled by distributions with reproducible statistics. It offers the recursive estimation of dynamic mixtures, which are free of iterative processes and close to analytical solutions as much as possible. In addition, these methods can be used online and simultaneously perform learning, which improves their efficiency during estimation. The book includes detailed program codes for solving the presented theoretical tasks. Codes are implemented in the open source platform for engineering computations. The program codes given serve to illustrate the theory and demonstrate the work of the included algorithms.
410  0$aSpringerBriefs in Statistics,$x2191-5458
606   $aProbabilities
606   $aStatistics
606   $aSystem theory
606   $aControl theory
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606   $aAlgorithms
606   $aProbability Theory
606   $aStatistical Theory and Methods
606   $aSystems Theory, Control
606   $aComputer Modelling
606   $aAlgorithms
615  0$aProbabilities.
615  0$aStatistics.
615  0$aSystem theory.
615  0$aControl theory.
615  0$aComputer simulation.
615  0$aAlgorithms.
615 14$aProbability Theory.
615 24$aStatistical Theory and Methods.
615 24$aSystems Theory, Control.
615 24$aComputer Modelling.
615 24$aAlgorithms.
676   $a519.544
700   $aNagy$b Ivan$4aut$4http://id.loc.gov/vocabulary/relators/aut$0766766
702   $aSuzdaleva$b Evgenia$4aut$4http://id.loc.gov/vocabulary/relators/aut
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