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020 _a9780750335911
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020 _a9780750335904
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020 _z9780750335898
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020 _z9780750335928
_qmyPrint
024 7 _a10.1088/978-0-7503-3591-1
_2doi
035 _a(CaBNVSL)thg00083531
035 _a(OCoLC)1358413932
040 _aCaBNVSL
_beng
_erda
_cCaBNVSL
_dCaBNVSL
050 4 _aTK5102.9
_b.I453 2022eb
072 7 _aUYS
_2bicssc
072 7 _aTEC067000
_2bisacsh
082 0 4 _a621.382/2
_223
100 1 _aIglesias Mart�inez, Miguel Enrique,
_eauthor.
_970902
245 1 0 _aAlgorithms for noise reduction in signals :
_btheory and practical examples based on statistical and convolutional analysis /
_cMiguel Enrique Iglesias Mart�inez, Miguel �Angel Garc�ia March, Carles Mili�an Enrique and Pedro Fern�andez de C�ordoba.
264 1 _aBristol [England] (Temple Circus, Temple Way, Bristol BS1 6HG, UK) :
_bIOP Publishing,
_c[2022]
300 _a1 online resource (various pagings) :
_billustrations.
336 _atext
_2rdacontent
337 _aelectronic
_2isbdmedia
338 _aonline resource
_2rdacarrier
490 1 _a[IOP release $release]
490 1 _aIOP ebooks. [2022 collection]
500 _a"Version: 20221201"--Title page verso.
504 _aIncludes bibliographical references.
505 0 _a1. Introduction -- 2. Current trends in signal processing techniques applied to noise reduction -- 2.1. Signals and noise -- 2.2. Current trends in signal processing techniques applied to noise reduction -- 2.3. Introduction to higher-order statistical analysis
505 8 _a3. Noise reduction in periodic signals based on statistical analysis -- 3.1. Basic approach to noise reduction using higher-order noise reduction statistics -- 3.2. Amplitude correction in the spectral domain -- 3.3. Experimental results applying the phase recovery algorithm -- 3.4. Computational cost analysis of the proposed method compared with others -- 3.5. SNR levels processed by the proposed algorithm compared with others developed for noise reduction and phase retrieval -- 3.6. Comparative analysis according to other noise reduction methods not based on HOSA -- 3.7. Application to noise reduction in real signals -- 3.8. Conclusions of the chapter
505 8 _aAppendix A. Properties of cumulants -- Appendix B. Moments, cumulants, and higher-order spectra -- Appendix C. Calculation of the one-dimensional component of the fourth-order cumulative of a harmonic signal -- Appendix D. Calculation of the autocorrelation function of a harmonic signal -- Appendix E. Examples of codes.
520 3 _aThis book is the result of an exhaustive review of the general algorithms used for noise reduction using two general application criteria: one-input, one-output systems, and two-input, one-output systems.
521 _aEngineers and scientists involved with nose reduction and signal processing.
530 _aAlso available in print.
538 _aMode of access: World Wide Web.
538 _aSystem requirements: Adobe Acrobat Reader, EPUB reader, or Kindle reader.
545 _aMiguel Enrique Iglesias Mart�inez: received a degree in Telecommunications and Electronics Engineering from the University of Pinar del R�io (UPR) in 2008 and a Master's Degree in Digital Systems from the Technological University of Havana, Cuba, in 2011.
588 0 _aTitle from PDF title page (viewed on January 9, 2023).
650 0 _aSignal processing
_xDigital techniques.
_93369
650 0 _aElectronic noise.
_94889
650 7 _aSignal processing.
_2bicssc
_94052
650 7 _aTECHNOLOGY & ENGINEERING / Signals & Signal Processing.
_2bisacsh
_96567
700 1 _aGarc�ia March, Miguel �Angel,
_eauthor.
_970903
700 1 _aMili�an Enrique, Carles,
_eauthor.
_970904
700 1 _aFern�andez de C�ordoba, Pedro,
_eauthor.
_970905
710 2 _aInstitute of Physics (Great Britain),
_epublisher.
_911622
776 0 8 _iPrint version:
_z9780750335898
_z9780750335928
830 0 _aIOP (Series).
_pRelease 22.
_970906
830 0 _aIOP ebooks.
_p2022 collection.
_970907
856 4 0 _uhttps://iopscience.iop.org/book/mono/978-0-7503-3591-1
942 _cEBK
999 _c82927
_d82927