- Neu
Decomposition, Entropy, and Machine Learning
Buch, Englisch, 83 Seiten, Format (B × H): 155 mm x 235 mm
Reihe: SpringerBriefs in Energy
ISBN: 978-3-032-11853-0
Verlag: Springer
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.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
- Technische Wissenschaften Energietechnik | Elektrotechnik Elektrotechnik
- Technische Wissenschaften Energietechnik | Elektrotechnik Alternative und erneuerbare Energien
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen
- Technische Wissenschaften Energietechnik | Elektrotechnik Energieverteilung, Stromnetze
Weitere Infos & Material
Introduction.- Signal decomposition methods.- Entropy analysis methods.- Machine learning methods.- Signal denoising applications.- Pattern recognition applications.- Conclusion.




