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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.
Key Features:
- Emphasis on noise reduction techniques
- Accompanying codes
- Interactive elements
- Practical approach
Preface
Acknowledgement
Author biography Glossary
1 Introduction 2 Current trends in signal processing techniques applied to noise reduction
3 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