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Algorithms for noise reduction in signals : theory and practical examples based on statistical and convolutional analysis /
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.
| Cote: | Libro Electrónico |
|---|---|
| Auteurs principaux: | , , , |
| Format: | Électronique eBook |
| Langue: | Inglés |
| Publié: |
Bristol [England] (Temple Circus, Temple Way, Bristol BS1 6HG, UK) :
IOP Publishing,
[2022]
|
| Collection: | IOP (Series). Release 22.
IOP ebooks. 2022 collection. |
| Sujets: | |
| Accès en ligne: | Texto completo |
Table des matières:
- 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.