02791nam 22006135 450 991104921670332120260102120824.03-032-11854-910.1007/978-3-032-11854-7(CKB)44769877200041(MiAaPQ)EBC32471210(Au-PeEL)EBL32471210(DE-He213)978-3-032-11854-7(EXLCZ)994476987720004120260102d2025 u| 0engur|||||||||||txtrdacontentcrdamediacrrdacarrierAdvanced Signal Processing Decomposition, Entropy, and Machine Learning /by Yuning Zhang, Chenxin Yang, Peng Luo, Heng Zhang1st ed. 2025.Cham :Springer Nature Switzerland :Imprint: Springer,2025.1 online resource (93 pages)SpringerBriefs in Energy,2191-55393-032-11853-0 Introduction -- Signal decomposition methods -- Entropy analysis methods -- Machine learning methods -- Signal denoising applications -- Pattern recognition applications -- Conclusion.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.SpringerBriefs in Energy,2191-5539Electric power distributionWater-powerElectrical engineeringMachine learningEnergy Grids and NetworksHydroenergyElectrical and Electronic EngineeringMachine LearningElectric power distribution.Water-power.Electrical engineering.Machine learning.Energy Grids and Networks.Hydroenergy.Electrical and Electronic Engineering.Machine Learning.321.319Zhang Yuning1732309MiAaPQMiAaPQMiAaPQBOOK9911049216703321Advanced Signal Processing4521894UNINA