000 | 03265nam a22005895i 4500 | ||
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001 | 978-3-540-68479-4 | ||
003 | DE-He213 | ||
005 | 20161121231201.0 | ||
007 | cr nn 008mamaa | ||
008 | 100301s2007 gw | s |||| 0|eng d | ||
020 |
_a9783540684794 _9978-3-540-68479-4 |
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024 | 7 |
_a10.1007/978-3-540-68479-4 _2doi |
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050 | 4 | _aTK7800-8360 | |
050 | 4 | _aTK7874-7874.9 | |
072 | 7 |
_aTJF _2bicssc |
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072 | 7 |
_aTEC008000 _2bisacsh |
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072 | 7 |
_aTEC008070 _2bisacsh |
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082 | 0 | 4 |
_a621.381 _223 |
100 | 1 |
_aDietl, Guido K.E. _eauthor. |
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245 | 1 | 0 |
_aLinear Estimation and Detection in Krylov Subspaces _h[electronic resource] / _cby Guido K.E. Dietl. |
264 | 1 |
_aBerlin, Heidelberg : _bSpringer Berlin Heidelberg, _c2007. |
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300 |
_aXX, 232 p. 94 illus. _bonline resource. |
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336 |
_atext _btxt _2rdacontent |
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337 |
_acomputer _bc _2rdamedia |
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338 |
_aonline resource _bcr _2rdacarrier |
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347 |
_atext file _bPDF _2rda |
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490 | 1 |
_aFoundations in Signal Processing, Communications and Networking, _x1863-8538 ; _v1 |
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505 | 0 | _aTheory: Linear Estimation in Krylov Subspaces -- Efficient Matrix Wiener Filter Implementations -- Block Krylov Methods -- Reduced-Rank Matrix Wiener Filters in Krylov Subspaces -- Application: Iterative Multiuser Detection -- System Model for Iterative Multiuser Detection -- System Performance -- Conclusions. | |
520 | _aThis book focuses on the foundations of linear estimation theory which is essential for effective signal processing. In its first part, it gives a comprehensive overview of several key methods like reduced-rank signal processing and Krylov subspace methods of numerical mathematics. Based on the derivation of the multistage Wiener filter in its most general form, the relationship between statistical signal processing and numerical mathematics is presented. In the second part, the theory is applied to iterative multiuser detection receivers (Turbo equalization) which are typically desired in wireless communication systems. The investigations include -exact computational complexity considerations and - performance analysis based on extrinsic information transfer charts as well as Monte-Carlo simulations. | ||
650 | 0 | _aEngineering. | |
650 | 0 |
_aComputer science _xMathematics. |
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650 | 0 | _aComputer mathematics. | |
650 | 0 | _aStatistics. | |
650 | 0 | _aApplied mathematics. | |
650 | 0 | _aEngineering mathematics. | |
650 | 0 | _aElectronics. | |
650 | 0 | _aMicroelectronics. | |
650 | 1 | 4 | _aEngineering. |
650 | 2 | 4 | _aElectronics and Microelectronics, Instrumentation. |
650 | 2 | 4 | _aSignal, Image and Speech Processing. |
650 | 2 | 4 | _aComputational Science and Engineering. |
650 | 2 | 4 | _aStatistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences. |
650 | 2 | 4 | _aMath Applications in Computer Science. |
650 | 2 | 4 | _aAppl.Mathematics/Computational Methods of Engineering. |
710 | 2 | _aSpringerLink (Online service) | |
773 | 0 | _tSpringer eBooks | |
776 | 0 | 8 |
_iPrinted edition: _z9783540684787 |
830 | 0 |
_aFoundations in Signal Processing, Communications and Networking, _x1863-8538 ; _v1 |
|
856 | 4 | 0 | _uhttp://dx.doi.org/10.1007/978-3-540-68479-4 |
912 | _aZDB-2-ENG | ||
950 | _aEngineering (Springer-11647) | ||
999 |
_c509783 _d509783 |