Classical Wavelet Packet Decomposition

Classical wavelet packet decomposition is a widely used signal analysis method that decomposes signals into sub-signals across different frequency bands to extract more detailed characteristic information. During the wavelet packet decomposition process, we can calculate the energy of each frequency band to obtain their respective energy values. By comparing these energy values across bands, we can derive energy ratios between different frequency bands, enabling deeper analysis of signal characteristics in the frequency domain. Implementation typically involves using wavelet packet transformation functions (e.g., wpdec in MATLAB) to decompose the signal into tree-structured nodes, followed by energy calculation for each node using squared norm operations. This approach not only provides spectral information but also computes parameters like inter-band energy ratios, offering enhanced insights for signal processing and analysis tasks. Key steps include selecting appropriate wavelet bases, determining decomposition levels, and implementing energy aggregation algorithms for quantitative frequency distribution analysis.