Algorithms for noise reduction in signals : theory and practical examples based on statistical and convolutional analysis / Miguel Enrique Iglesias Mart�inez, Miguel �Angel Garc�ia March, Carles Mili�an Enrique and Pedro Fern�andez de C�ordoba.
By: Iglesias Mart�inez, Miguel Enrique [author.]
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Contributor(s): Garc�ia March, Miguel �Angel [author.] | Mili�an Enrique, Carles [author.] | Fern�andez de C�ordoba, Pedro [author.] | Institute of Physics (Great Britain) [publisher.].
Material type: 
BookSeries: IOP (Series)Release 22: ; IOP ebooks2022 collection: Publisher: Bristol [England] (Temple Circus, Temple Way, Bristol BS1 6HG, UK) : IOP Publishing, [2022]Description: 1 online resource (various pagings) : illustrations.Content type: text Media type: electronic Carrier type: online resourceISBN: 9780750335911; 9780750335904.Subject(s): Signal processing -- Digital techniques | Electronic noise | Signal processing | TECHNOLOGY & ENGINEERING / Signals & Signal ProcessingAdditional physical formats: Print version:: No titleDDC classification: 621.382/2 Online resources: Click here to access online Also available in print."Version: 20221201"--Title page verso.
Includes bibliographical references.
1. 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
3. 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
Appendix 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.
This 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.
Engineers and scientists involved with nose reduction and signal processing.
Also available in print.
Mode of access: World Wide Web.
System requirements: Adobe Acrobat Reader, EPUB reader, or Kindle reader.
Miguel 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.
Title from PDF title page (viewed on January 9, 2023).
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