Comprehensive Guide to Source Separation: Delve into the fundamentals and advanced techniques of source separation, including blind source separation, independent component analysis, and subspace methods.

Machine Learning Integration: Explore the integration of machine learning algorithms into source separation, enhancing performance and enabling real-world applications.

Practical Applications: Discover practical applications of source separation in fields such as audio signal processing, speech enhancement, and biomedical signal analysis.

Case Studies and Examples: Engage with real-world case studies and examples to illustrate the practical implementation of source separation techniques.

* Up-to-Date Research: Stay informed with the latest advancements in source separation and machine learning, providing a solid foundation for further research and development.