Wavelet Packet Transform for Signal Analysis

Wavelet Packet Transform (WPT) represents a classical signal analysis method that can be implemented in MATLAB through specialized wavelet analysis programming for effective signal denoising applications. The core computational procedures involve wavelet decomposition and reconstruction stages, where signals are broken down into different frequency components and then reassembled to extract meaningful information. This implementation demonstrates key MATLAB functions such as wpdec for wavelet packet decomposition and wprcoef for reconstruction, employing entropy-based criterion for optimal node selection. The algorithm follows a tree-structured approach where signals undergo multi-level decomposition using filter banks, with thresholding techniques applied to wavelet coefficients for noise removal. This classic program provides comprehensive insights into practical wavelet analysis implementation, offering learners a structured approach to understanding WPT computational processes including coefficient thresholding, inverse transformation, and signal fidelity evaluation metrics.