Algorithms for Noise Reduction in Signals: Theory and practical examples based on statistical and convolutional analysisКНИГИ » ТЕХНИЧЕСКИЕ НАУКИ
Название: Algorithms for Noise Reduction in Signals: Theory and practical examples based on statistical and convolutional analysis Автор: Miguel Enrique Iglesias Mart?nez, Miguel Angel Garc?a March, Carles Milian Enrique and Pedro Fernandez de Cordoba Издательство: IOP Publishing Год: 2022 Формат: PDF Страниц: 110 Размер: 19,27 MB Язык: English
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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Algorithms for Noise Reduction in Signals: Theory and practical examples based on statistical and convolutional analysis 
