MWORKS Syslab Online

Browser-based scientific computing with Julia. No installation required.

simulation.jl
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x(t)Time (s)
Output rendered

Try It Yourself

Run Julia code directly in your browser. No installation required.

Visualize how small changes in initial conditions lead to unpredictable outcomes.

chaos.jl
# Lorenz System - Sensitive Dependence
using MWorks, Plots, DifferentialEquations

function lorenz!(du, u, p, t)
    σ, ρ, β = p
    du[1] = σ * (u[2] - u[1])
    du[2] = u[1] * (ρ - u[3]) - u[2]
    du[3] = u[1] * u[2] - β * u[3]
end

u0 = [1.0; 0.0; 0.0]
p = [10.0, 28.0, 8/3]
tspan = (0.0, 50.0)

prob = ODEProblem(lorenz!, u0, tspan, p)
sol = solve(prob)

plot(sol, vars=(1,2,3), lw=0.5)
title!("Lorenz Attractor")
Output
Click Run Code to see output

Signal Processing & Communications

Analyze sampled signals, design digital filters, and visualize frequency content.

Automation & Control Systems

Model dynamic systems, design controllers, and deploy via auto-generated code.

Data Science & AI

Perform clustering, classification, and train neural networks for predictive modeling.

Image Processing & Vision

Segment, filter, and enhance images. Build computer vision pipelines.

Built for Engineers & Scientists

General-Purpose Programming & Algorithms

  • Interactive Julia development environment
  • Python and M language compatibility
  • Cross-language integration (C/C++, Fortran)
  • Full debugging and profiling support

High-Performance Math Engine

  • Symbolic computation & curve fitting
  • Optimization & global optimization
  • Concise expression for complex problems
  • JIT-compiled for maximum efficiency

Data Analysis & Visualization

  • Import MAT, CSV, TXT, Excel, HDF5, JSON
  • Data preprocessing & statistical analysis
  • Publication-ready scientific graphics
  • Customizable annotations & tooltips

Professional Toolboxes

  • Signal processing & wireless communications
  • Control systems toolbox
  • AI & data science toolkit
  • Extensible platform architecture

Three Simple Steps

01

Write Julia Code

Use familiar Julia syntax with MWorks extensions for modeling and simulation.

using MWorks model = System()
02

Run Simulation

Execute your model with high-performance solvers optimized for engineering problems.

result = solve(model) plot(result)
03

Analyze Results

Visualize and export results for further analysis or integration with other tools.

export(result, "csv") generate_report()

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