MATLAB Code Implementation for Continuous Wavelet Transform

This MATLAB implementation provides a working code solution for continuous Wavelet Transform (CWT). Continuous Wavelet Transform is a powerful signal processing technique extensively used in image processing, audio analysis, and video processing applications. The algorithm decomposes signals into different frequency bands across multiple scales while extracting both time-domain and frequency-domain characteristics. In MATLAB implementation, the cwt() function from the Wavelet Toolbox serves as the primary function for performing continuous wavelet transform. The code demonstrates proper parameter configuration including: - Selection of appropriate wavelet basis functions (e.g., Morse, Morlet, or bump wavelets) - Scale parameter specification for frequency resolution control - Sampling frequency setup for accurate time-frequency representation Key implementation aspects covered: 1. Signal preprocessing and normalization 2. Wavelet coefficient computation using convolution operations 3. Time-frequency visualization through scalogram plots 4. Inverse transform validation for reconstruction accuracy This implementation serves as an educational template for applying CWT to custom projects, featuring commented code sections that explain algorithm steps and parameter tuning considerations. The debugged code ensures reliable performance and provides a foundation for extending to multi-dimensional signal analysis.