Generating Narrowband Random Processes Using Rice Representation of Stochastic Processes

Generating narrowband random processes based on Rice representation of stochastic processes, including mastering their key characteristics such as mean (mathematical expectation), variance, correlation function, and power spectral density through implementation approaches involving random variable generation and spectral analysis techniques.

Generation and Analysis of a Narrowband Random Process with Computational Methods

Implementation in MATLAB for generating a conditional narrowband random process, including subroutines to compute mean function, autocorrelation function, power spectrum, envelope, squared envelope, and phase characteristics with one-dimensional probability density visualization