Gaussian Mixture Model with Expectation-Maximization Algorithm for Parameter Estimation

A parameter estimation model for Gaussian mixture distributions using the Expectation-Maximization algorithm, applicable in communication systems, signal processing, and statistical analysis with implementation-ready algorithmic frameworks.

Gaussian Mixture Model EM Algorithm

The Gaussian Mixture Model EM Algorithm calculates three key parameters for Gaussian mixture distributions, which better approximate coefficient distributions than single Gaussian models. Implementation involves iterative expectation and maximization steps for parameter estimation.