MATLAB Implementation of Non-Gaussian Noise

This MATLAB-implemented non-Gaussian noise program offers practical utility for understanding and analyzing non-Gaussian noise characteristics. The code implements various non-Gaussian distributions including alpha-stable, Gamma, or Laplace distributions through probability density functions and random number generation algorithms. Key functions like stable.randn() for alpha-stable noise or gamrnd() for Gamma distribution provide flexible parameter customization for different noise scenarios. The program's structured implementation makes it accessible even for users unfamiliar with non-Gaussian noise concepts, featuring clear commenting and modular design. Advanced functionalities include statistical analysis tools for measuring noise kurtosis and skewness, time-frequency analysis capabilities, and comparison features against Gaussian benchmarks. For researchers, the code supports custom distribution parameters, noise superposition methods, and performance evaluation metrics. The implementation demonstrates practical techniques for generating correlated non-Gaussian sequences using copula functions or nonlinear transformations. Whether for academic study or professional signal processing applications, this program serves as a comprehensive toolbox with both educational and research value, featuring robust error handling and visualization components for immediate practical deployment.