Iglesias Martínez M.E., Garcı´a March M.Á., Enrique C.M., de Córdoba P.F. Algorithms for Noise Reduction in Signals: Theory and practical examples based on statistical and convolutional analysis

IOP Publishing Ltd, 2022. — 111 p.The present book is the result of a review of the most general techniques for the treatment of noise from the point of view of a system composed of one input and one output or two inputs and one output in the case of adaptive and artificial intelligence models and their foundations based on statistical analysis.
The first part introduces the concepts of signal and processing in a communication system, as well as different algorithms applied to noise reduction and recovery of phase information in contaminated signals. Subsequently, the book focuses on the treatment of noise using statistical processing based on nonparametric estimates of statistical characteristics such as cumulants, moments, and higher-order spectra, presenting several results from a practical point of view and in real situations.Introduction
Current trends in signal processing techniques applied to noise reduction
Noise reduction in periodic signals based on statistical analysis
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