Abstract
Efficient compression of speech and biomedical signals is essential for reducing storage and transmission costs while ensuring high fidelity in reconstruction. Traditional scalar, vector, and transform-based methods, though effective, face challenges in handling non-stationary signals and maintaining robustness in noisy environments.