Intrinsic Time-Scale Decomposition – A Novel Signal Decomposition Approach

In this document, we introduce a novel signal decomposition technique known as Intrinsic Time-Scale Decomposition (ITD). This method is characterized by its straightforward algorithm, rapid execution speed, and computational efficiency. ITD serves as a powerful tool for signal processing and analysis, enabling the decomposition of complex signals into distinct time-scale components. This decomposition facilitates a deeper understanding of signal characteristics and temporal variations. By implementing ITD, one can extract additional information from signals and perform more refined analysis and processing at different scales. The algorithm typically involves iterative separation of baseline and detail components using local extrema detection and linear interpolation techniques. Its applications span various domains including audio processing, image analysis, and financial data examination. In summary, Intrinsic Time-Scale Decomposition represents a robust and effective signal decomposition methodology that provides enhanced insights and broad practical implementation possibilities.