Particle Filter Resampling (13 Methods with MATLAB Implementation)

I have developed a comprehensive collection of resampling methods for particle filtering in MATLAB, organized in separate .m files as attached below. These implementations cover various algorithmic approaches including systematic resampling, residual resampling, multinomial resampling, and several optimized variants. Each method includes proper weight normalization, particle redistribution, and efficient random number generation techniques suitable for real-time applications. The code implementations feature: - Efficient vectorized operations for better performance - Proper handling of degenerate particle weights - Memory-efficient sampling algorithms - Compatibility with standard particle filter frameworks You may find these implementations useful for your research or applications, and I welcome any suggestions for improvement or alternative approaches. If you have any technical questions about the implementation details, algorithmic choices, or practical applications, I would be happy to provide additional explanations, detailed code comments, or usage examples. Please feel free to contact me for further discussion about these resampling techniques or potential collaborations.