Year: 2025
Type: preprint
Abstract: This experiment aims to generate Gaussian white noise using a custom algorithm based on the Generalized Mapping Theory (GMT) and verify the statistical properties of the generated signal. Through the Central Limit Theorem (CLT), uniform distributions are transformed into a Gaussian distribution, and the Kolmogorov-Smirnov (KS) test and visualization techniques are employed to evaluate the quality of the generated noise. The results demonstrate that the generated signal closely approximates the target Gaussian distribution with a mean of 0 and a standard deviation of 1.
DOI: 10.31224/5099
Author: 洪涛 凌
Institution: Anhui Institute of International Business
Language: English
Subfield: Statistics and Probability
Field: Mathematics
Domain: Physical Sciences
Open Access status: gold
OpenAlex ID: W4413379851