In the realm of education, moments of appreciation often come as rays of sunshine, reminding educators of the profound effect their efforts can have on their students' lives. Recently, such a moment unfolded in the form of a small yet incredibly gesture from one of the students enrolled in the TSKS01: Digital Communications course at Linköping University (LiU), Sweden.

In this blog post, we’ll explore the connections among conditional mean, variance, conditional Probability Density Functions (PDFs), and also its relationship with Minimum Mean Square Error (MMSE) estimator. Conditional Probability Density Function Consider two random variables, $X$ and $Y$ (which could be complex).

Welcome to this blog post, where we will learn to generate random variable (RV) using three popular programming languages: MATLAB, Python, and C++. Our focus will be on various types of random variables, including uniform, Gaussian, and Laplacian distributions, or any other distribution with a known inverse Cumulative Distribution Function (CDF).