Wavelet Transform Implementation Using MATLAB

This program implements wavelet transform algorithms using MATLAB's Signal Processing Toolbox. The core functionality includes performing 4-level wavelet decomposition and reconstruction of input signals. Wavelet decomposition is a signal processing technique that breaks down signals into different frequency components through multi-resolution analysis, enabling better understanding and analysis of signal characteristics. The reconstruction process synthesizes the decomposed components back to the original signal. Key implementation features include: - Utilization of MATLAB's built-in wavelet functions (wavedec, waverec) for efficient computation - Customizable wavelet types (Daubechies, Haar, etc.) through function parameters - Step-by-step decomposition coefficients extraction using appcoef and detcoef functions - Visualization of approximation and detail coefficients at each decomposition level This program provides researchers and engineers with a comprehensive toolkit for advanced signal analysis, feature extraction, and noise reduction applications in various domains including biomedical signal processing, audio analysis, and vibration monitoring.