DISCOVER WAVELET APPROACH FOR TIME SERIES ANALYSIS

This book offers an accessible introduction to wavelet theory, designed for readers with little or no prior background in the field. It presents the fundamental concepts of wavelets, explaining how they differ from traditional methods and why they are particularly effective for analyzing non-stationary signals. Through clear explanations and illustrative examples, the book covers key types of wavelet transforms—such as the Continuous Wavelet Transform (CWT), Discrete Wavelet Transform (DWT), and Maximum Overlap DWT (MODWT)—as well as real-world applications in signal processing, time series analysis, ... Structured in three chapters, it combines theoretical foundations with practical insights to make learning wavelets both intuitive and applicable.