Algorithms for Noise Reduction in Signals Theory and practical examples based on statistical and convolutional analysis

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Algorithms for Noise Reduction in Signals: Theory and practical examples based on statistical and convolutional analysis
by Miguel Enrique Iglesias Martínez, Miguel Ángel García March, Carles Milián Enrique and Pedro Fernández de Córdoba
English | 2022 | ISBN: 978-0-7503-3591-1 | 110 pages | True PDF EPUB MOBI | 31.44 MB

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. The text describes theoretically and experimentally the processes related to high-order statistical analysis algorithms, as well as its practical combination with the convolutional analysis. On the other hand, the results of applications in real telecommunications signals, sensing of variables and biosignals such as human tremor are also shown. The reader will benefit from both the theoretical foundations described in the book, and the practical examples including generic codes of all the functions described and modifiable for use in different applications. This book is an ideal text for engineers, graduate students and scientists involved with noise reduction and signal processing.

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