Algorithms for noise reduction in signals : theory and practical examples based on statistical and convolutional analysis / Miguel Enrique Iglesias Martínez, Miguel Ángel García March, Carles Milián Enrique and Pedro Fernández de Córdoba.

Format:

Book

Author/Creator:

Iglesias Martínez, Miguel Enrique, author.

García March, Miguel Ángel, author.

Milián Enrique, Carles, author.

Fernández de Córdoba, Pedro, author.

Contributor:

Institute of Physics (Great Britain), publisher.

Series:

IOP (Series). Release 22.

IOP ebooks. 2022 collection.

[IOP release $release]

IOP ebooks. [2022 collection]

Language:

English

Subjects (All):

Signal processing--Digital techniques.

Signal processing.

Electronic noise.

Physical Description:

1 online resource (various pagings) : illustrations.

Place of Publication:

Bristol [England] (Temple Circus, Temple Way, Bristol BS1 6HG, UK) : IOP Publishing, [2022]

System Details:

Mode of access: World Wide Web.

System requirements: Adobe Acrobat Reader, EPUB reader, or Kindle reader.

Biography/History:

Miguel Enrique Iglesias Martínez: received a degree in Telecommunications and Electronics Engineering from the University of Pinar del Río (UPR) in 2008 and a Master's Degree in Digital Systems from the Technological University of Havana, Cuba, in 2011.

Summary:

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.

Contents:

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.

Notes:

"Version: 20221201"--Title page verso.

Includes bibliographical references.

Title from PDF title page (viewed on January 9, 2023).

Other Format:

Print version:

ISBN:

9780750335911

9780750335904

OCLC:

1358413932

Access Restriction:

Restricted for use by site license.