Explore MATLAB source code curated for "随机变量" with clean implementations, documentation, and examples.
Computes joint probability density functions for multiple random variables with visualization capabilities, supporting distributions including Normal, Poisson, Gamma, and other common statistical functions with correlation analysis features.
Core source code for Monte Carlo method implementation, providing multiple distribution types for random variables with ready-to-use functionality.
This internationally sourced MATLAB toolbox efficiently computes mutual information and entropy for random variables, featuring probabilistic distribution functions, stochastic process modeling, and signal processing applications with comprehensive documentation.
BPSK System Simulation This implementation models the generation of random variables r0 and r1 representing received signal components. These variables serve as inputs to the detection mechanism, where the detector output is systematically compared against the original binary transmission sequence. An error counting algorithm tracks bit error occurrences, enabling quantitative performance evaluation through parameters like signal-to-noise ratio and coding rate adjustments.
A MATLAB script implementing methods to generate Gaussian distributed random variables, providing convenient generation of normally distributed random numbers with customizable parameters.
Generating Random Variables Across up to 50 Probability Distributions