Simulation of Brownian Motion Generation

Simulating Brownian motion generation in MATLAB environment strengthens the comprehension of stochastic phenomena. Brownian motion represents a random process characterized by unpredictable trajectory patterns. Implementing Brownian motion simulation in MATLAB enables deeper investigation into this stochastic phenomenon, revealing its underlying principles and properties. Through MATLAB simulation, we can better understand applications of random phenomena across physics, chemistry, and biological fields - such as protein molecule diffusion. The implementation typically involves generating random increments using MATLAB's randn() function for normal distribution, cumulative summation via cumsum() for path construction, and visualization through plot() functions. This MATLAB-based Brownian motion simulation provides valuable assistance for related research domains by offering customizable parameters like step size, time intervals, and multidimensional trajectory generation capabilities.