Advanced Signal Processing
Decomposition, Entropy, and Machine Learning
Series: SpringerBriefs in Energy;
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22 184 Ft (21 128 Ft + 5% VAT)
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22 184 Ft
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Product details:
- Publisher Springer Nature Switzerland
- Date of Publication 9 January 2026
- ISBN 9783032118530
- Binding Paperback
- No. of pages90 pages
- Size 235x155 mm
- Language English
- Illustrations VIII, 90 p. 44 illus., 25 illus. in color. 700
Categories
Long description:
This brief explores advanced signal processing techniques, focusing on signal decomposition, entropy analysis, and machine learning, with applications in energy-related fields such as hydroturbines, wind turbines, and power grids. It provides a detailed overview of methods for signal denoising and pattern recognition, covering techniques like wavelet transform, empirical mode decomposition, permutation entropy, and deep learning models. Through real-world engineering case studies, the book demonstrates how these methods enhance data analysis, improve fault detection, and optimize system performance, making it a valuable resource for researchers, engineers, and students in signal processing and mechanical engineering.
MoreTable of Contents:
Introduction.- Signal decomposition methods.- Entropy analysis methods.- Machine learning methods.- Signal denoising applications.- Pattern recognition applications.- Conclusion.
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