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02385nam a22004215i 4500 |
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978-3-642-29396-2 |
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20151125162040.0 |
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121026s2013 gw | s |||| 0|eng d |
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|a 9783642293962
|9 978-3-642-29396-2
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|a 10.1007/978-3-642-29396-2
|2 doi
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|a QA276-280
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|a MAT029000
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|a 519.5
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|a Śliwiński, Przemysław.
|e author.
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|a Nonlinear System Identification by Haar Wavelets
|h [electronic resource] /
|c by Przemysław Śliwiński.
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|a Berlin, Heidelberg :
|b Springer Berlin Heidelberg :
|b Imprint: Springer,
|c 2013.
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|a XI, 139 p. 27 illus., 18 illus. in color.
|b online resource.
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|a text
|b txt
|2 rdacontent
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|a computer
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|a online resource
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|a text file
|b PDF
|2 rda
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|a Lecture Notes in Statistics,
|x 0930-0325 ;
|v 210
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|a Introduction -- Hammerstein systems -- Identification goal -- Haar orthogonal bases -- Identification algorithms -- Computational algorithms. – Final remarks. - Technical derivations.
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|a In order to precisely model real-life systems or man-made devices, both nonlinear and dynamic properties need to be taken into account. The generic, black-box model based on Volterra and Wiener series is capable of representing fairly complicated nonlinear and dynamic interactions, however, the resulting identification algorithms are impractical, mainly due to their computational complexity. One of the alternatives offering fast identification algorithms is the block-oriented approach, in which systems of relatively simple structures are considered. The book provides nonparametric identification algorithms designed for such systems together with the description of their asymptotic and computational properties.
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|a Statistics.
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|a Statistics.
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|a Statistical Theory and Methods.
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|a SpringerLink (Online service)
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|t Springer eBooks
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|i Printed edition:
|z 9783642293955
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|a Lecture Notes in Statistics,
|x 0930-0325 ;
|v 210
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|u http://dx.doi.org/10.1007/978-3-642-29396-2
|z Full Text via HEAL-Link
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|a ZDB-2-SMA
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|a Mathematics and Statistics (Springer-11649)
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