Spectrum Subtraction Algorithm - A Popular Shared Implementation

Here is a proposal to further enhance the currently popular shared spectrum subtraction program. While the existing implementation already provides comprehensive functionality, we can integrate additional features to increase its utility for users. Key technical enhancements could include: - Implementing a sensitivity adjustment parameter that controls the subtraction threshold using dynamic weighting functions - Adding an automated background noise correction module utilizing adaptive filtering algorithms (e.g., LMS or Kalman filter implementations) - Integrating spectral smoothing functions through moving average or Savitzky-Golay filters to reduce high-frequency artifacts From a code implementation perspective, we could: - Create modular functions for each processing stage (pre-processing, subtraction, post-processing) - Implement configurable parameters through a structured configuration class or JSON configuration files - Add real-time visualization capabilities using plotting libraries to monitor spectral changes Additionally, comprehensive documentation should include: - A detailed user manual explaining parameter tuning and algorithm selection - Tutorial videos demonstrating practical application scenarios with code examples - API documentation for developers wishing to extend the functionality By incorporating these technical improvements and documentation enhancements, we can create a more user-friendly and robust spectrum subtraction tool that benefits both novice and advanced users in signal processing applications.