000 | 03375nam a22005055i 4500 | ||
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001 | 978-81-322-0628-6 | ||
003 | DE-He213 | ||
005 | 20140220083334.0 | ||
007 | cr nn 008mamaa | ||
008 | 120523s2012 ii | s |||| 0|eng d | ||
020 |
_a9788132206286 _9978-81-322-0628-6 |
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024 | 7 |
_a10.1007/978-81-322-0628-6 _2doi |
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050 | 4 | _aQA276-280 | |
072 | 7 |
_aUFM _2bicssc |
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072 | 7 |
_aCOM077000 _2bisacsh |
|
082 | 0 | 4 |
_a519.5 _223 |
100 | 1 |
_aKundu, Debasis. _eauthor. |
|
245 | 1 | 0 |
_aStatistical Signal Processing _h[electronic resource] : _bFrequency Estimation / _cby Debasis Kundu, Swagata Nandi. |
264 | 1 |
_aIndia : _bSpringer India : _bImprint: Springer, _c2012. |
|
300 |
_aXVII, 132 p. 21 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 |
||
490 | 1 |
_aSpringerBriefs in Statistics, _x2191-544X |
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505 | 0 | _a1 Introduction -- 2 Notations and Preliminaries -- 3 Estimation of Frequencies -- 4 Asymptotic Properties -- 5 Estimating the Number of Components -- 6 Real Data Example -- 7 Multidimensional Models -- 8 Related Models -- References -- Index. | |
520 | _aSignal processing may broadly be considered to involve the recovery of information from physical observations. The received signal is usually disturbed by thermal, electrical, atmospheric or intentional interferences. Due to the random nature of the signal, statistical techniques play an important role in analyzing the signal. Statistics is also used in the formulation of the appropriate models to describe the behavior of the system, the development of appropriate techniques for estimation of model parameters and the assessment of the model performances. Statistical signal processing basically refers to the analysis of random signals using appropriate statistical techniques. The main aim of this book is to introduce different signal processing models which have been used in analyzing periodic data, and different statistical and computational issues involved in solving them. We discuss in detail the sinusoidal frequency model which has been used extensively in analyzing periodic data occuring in various fields. We have tried to introduce different associated models and higher dimensional statistical signal processing models which have been further discussed in the literature. Different real data sets have been analyzed to illustrate how different models can be used in practice. Several open problems have been indicated for future research. | ||
650 | 0 | _aStatistics. | |
650 | 0 | _aAlgorithms. | |
650 | 0 | _aMathematical statistics. | |
650 | 0 | _aEngineering mathematics. | |
650 | 1 | 4 | _aStatistics. |
650 | 2 | 4 | _aStatistics and Computing/Statistics Programs. |
650 | 2 | 4 | _aStatistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences. |
650 | 2 | 4 | _aAlgorithms. |
650 | 2 | 4 | _aAppl.Mathematics/Computational Methods of Engineering. |
700 | 1 |
_aNandi, Swagata. _eauthor. |
|
710 | 2 | _aSpringerLink (Online service) | |
773 | 0 | _tSpringer eBooks | |
776 | 0 | 8 |
_iPrinted edition: _z9788132206279 |
830 | 0 |
_aSpringerBriefs in Statistics, _x2191-544X |
|
856 | 4 | 0 | _uhttp://dx.doi.org/10.1007/978-81-322-0628-6 |
912 | _aZDB-2-SMA | ||
999 |
_c104062 _d104062 |