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Embedded code generation is fundamentally changing the way engineers work. Instead of writing thousands of lines of code by hand, engineers are automatically generating their production code to increase productivity, improve quality, and foster innovation.
With MathWorks embedded code generation products, you can:
Design real-time applications targeting floating- or fixed-point processors
Generate C and C++ code from MATLAB® and Simulink®
Optimize code for specific processor architectures
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Profile and verify embedded code on microcontrollers and DSPs
Address industry certification standards

Mathematical models are critical to understanding and accurately predicting the behavior of complex systems. These models enable critical tasks, such as:
Forecasting and optimizing system behavior
Designing control systems
Characterizing system response
MathWorks products provide all the tools you need to develop mathematical models. MATLAB® supports both numeric and symbolic modeling approaches and provides curve fitting, statistics, optimization, ODE and PDE solving, calculus, and other core mathematical tools. Simulink® adds an environment for modeling and simulating the behavior of multidomain systems and for developing embedded systems.

Behavioral Analog/Mixed-Signal Design
Modeling and simulating analog/mixed-** systems in circuit-level tools is time consuming and limits the number of design alternatives engineers can evaluate. By contrast, MATLAB and Simulink provide a higher level of design abstraction and faster modeling and simulation, which enables engineers to quickly evaluate numerous design options.
Semiconductor engineers use MATLAB and Simulink models as golden references when they create transistor-level circuit models. These MATLAB and Simulink models integrate with analog/mixed-** design tools such Cadence® Virtuoso® AMS Designer, and can also be used as behavioral verification models in production SystemVerilog test environments.

Discrete-event simulation with SimEvents® provides capabilities for analyzing and optimizing event-driven communication using hybrid system models, agent-based models, state charts, and process flows.
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Design distributed control systems, hardware architectures, and sensor and communication networks for aerospace, automotive, and electronics applications
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Customize queues, routing algorithms, processing delays, and prioritization schemes
Simulate hybrid systems containing time-based, event-based, and agent-based components
Simulate event-driven processes, such as mission plans with autonomous agents or the stages of a manufacturing process
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