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- Author: Miguel Enrique Iglesias MartÃnez
- Publisher: IOP Publishing Ltd
- ISBN-10: 0750335890
- ISBN-13: 9780750335898
- Format: 17.8 x 25.4 x 0.8 cm, hardcover
- Language: English
- SAVE -10% with code: EXTRA
Algorithms for Noise Reduction in Signals (e-book) (used book) | bookbook.eu
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Description
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
EXTRA 10 % discount with code: EXTRA
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- Author: Miguel Enrique Iglesias MartÃnez
- Publisher: IOP Publishing Ltd
- ISBN-10: 0750335890
- ISBN-13: 9780750335898
- Format: 17.8 x 25.4 x 0.8 cm, hardcover
- Language: English 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.
Key Features:
- Emphasis on noise reduction techniques
- Accompanying codes
- Interactive elements
- Practical approach
Reviews