Generalized Correlation Method with Maximum Likelihood (ML) Weighting Function - MATLAB Source Code

The generalized correlation method is a widely used signal processing technique applicable in various fields including image processing and machine learning. This implementation features a Maximum Likelihood (ML) form as the weighting function, which is optimized for statistical estimation accuracy. The MATLAB source code provides a complete implementation that includes data preprocessing routines and parameter optimization modules to achieve optimal processing performance. The algorithm implementation involves computing cross-correlation matrices and applying ML-based weighting to enhance signal correlation characteristics. Key functions include data normalization, covariance matrix calculation, and ML weight optimization. Furthermore, the generalized correlation method can be integrated with other techniques to address more complex problem scenarios, with the code structure allowing for modular extensions and combination with additional signal processing algorithms.