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https://github.com/ramy-badr-ahmed/random-simplex
Random Simplex - https://doi.org/10.5281/zenodo.12808899
https://github.com/ramy-badr-ahmed/random-simplex
fortran matlab multivariate-distributions random-simplex stability-analysis
Last synced: 11 days ago
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Random Simplex - https://doi.org/10.5281/zenodo.12808899
- Host: GitHub
- URL: https://github.com/ramy-badr-ahmed/random-simplex
- Owner: Ramy-Badr-Ahmed
- License: apache-2.0
- Created: 2024-07-14T23:34:04.000Z (5 months ago)
- Default Branch: main
- Last Pushed: 2024-08-12T09:38:47.000Z (4 months ago)
- Last Synced: 2024-10-25T04:24:25.464Z (about 2 months ago)
- Topics: fortran, matlab, multivariate-distributions, random-simplex, stability-analysis
- Language: MATLAB
- Homepage:
- Size: 1.02 MB
- Stars: 0
- Watchers: 1
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
![MATLAB](https://img.shields.io/badge/MATLAB-%23D00000.svg?style=plastic&logo=mathworks&logoColor=white) ![Fortran](https://img.shields.io/badge/Fortran-%23734F96.svg?style=plastic&logo=fortran&logoColor=white) ![GitHub](https://img.shields.io/github/license/Ramy-Badr-Ahmed/random-simplex?style=plastic)
[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.12808899.svg)](https://doi.org/10.5281/zenodo.12808899)
# Random Simplex Matrix
## Overview
This repository contains a function that utilises the Dirichlet distribution method to generate points on the `(n−1)`-dimensional simplex. The `randomSimplexMatrix.m` generates `m x n` matrices where each row is a random sample from the `(n−1)`-dimensional simplex, i.e., it produces vectors where each element is a non-negative number and the sum of all elements in each vector is 1.
### About
[Mathematica Link](https://reference.wolfram.com/language/ref/Simplex.html)
## Methodology
1. **Generation of K Unit-Exponential Distributed Random Draws**:
- In each row (sample), the function generates K uniform random numbers `y_i` from the open interval `(0,1]`.
- These are transformed to unit-exponential distributed random numbers `x_i = -log(y_i)`.2. **Normalization**:
- Compute the sum `S` of all `x_i` values.3. **Calculation of Simplex Coordinates**:
- The coordinates `t_1, ..., t_K` of the final point on the unit simplex are computed as `t_i = x_i / S`.4. **Output**:
- Returns a matrix, where each row is a vector on the `(n-1)`-dimensional simplex.## Some Applications
#### Stability Analysis
- Polynomial Stability/Stability of discrete-time control systems:
> Use simplex sampling to generate coefficients for polynomials and analyse their stability by checking if all roots lie within the unit circle.
- Lyapunov Functions:
> Construct Lyapunov functions with randomly sampled coefficients to study the stability of equilibrium points in dynamical systems.
#### Bifurcation Analysis
- Parameter Space Exploration:
> Investigate the behavior of dynamical systems under different parameter regimes by sampling parameters from a simplex. Identify bifurcation points where system behavior changes qualitatively.
- Nonlinear Dynamics:
> Model/simulate nonlinear systems to study chaos, where initial conditions or parameters are sampled from a simplex.
## Additional Scripts
1. `simplexSpace.m`
> Demonstrates various plots and visualisations of simplex sampling.
2. `MultivariateND.m`
> Showcases an application of simplex sampling for sampling from a multivariate normal distribution.
3. `VoronoiDiagram.m`
> Visualise the Voronoi diagram of random points on a 2-dimensional simplex, divides regions based on proximity.
## Example Usage
```matlab
n = 100; % Number of columns (dimensionality of simplex)
m = 1500; % Number of rows (number of samples)
y = randomSimplexMatrix(n, m);
disp('Generated simplex matrix:');
disp(y);
```