Engineers use MATLAB and Simulink product families to design and simulate signal and image processing systems and control systems by capturing algorithms and system models. Using MATLAB and Simulink you can:
- Analyze signals and explore algorithms
- Evaluate design implementation tradeoffs to build real-time signal processing systems
- Develop digital control systems for motors, power converters, and battery systems
- Accelerate the design of embedded systems that have interacting components
“Model-Based Design helped us apply the design and verification methods required by ISO 26262, including back-to-back verification and test coverage assessment. In particular, the automated test cases and reports in Simulink Test contributed significantly to reduced testing efforts.”
Signal Processing
Signal processing engineers use MATLAB and Simulink at all stages of development from analyzing signals to deploying real-time processing systems. MATLAB and Simulink offer:
- Built-in functions and apps for analysis and preprocessing of time-series data and spectral analysis, such as big data for predictive maintenance, anomaly detection, time frequency analysis, and signal measurement
- Apps and algorithms to design, analyze, and implement digital filters (FIR and IIR) from basic FIR and IIR filters to adaptive, multirate, and multistage design
- An environment to model and simulate signal processing systems with a combination of programs and block diagrams
- Capabilities to model fixed-point behavior and automatically generate C/C++ or HDL code for deploying on embedded processors, FPGAs, and ASICs
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Image Processing and Computer Vision
Engineers use MATLAB and Simulink tools to accelerate the design of embedded systems that have interacting components such as video, and user interface features found in phone or game systems. Engineers can model embedded systems using libraries of prebuilt components to speed design across a range of applications including accelerometers, image acquisition, image processing, surveillance, and image recognition. With MATLAB and Simulink you can:
- Design vision solutions with a comprehensive set of reference-standard algorithms for image processing, computer vision, and deep learning.
- Collaborate with teams using OpenCV, Python, and C/C++ using interoperable APIs and integration tools.
- Use workflow apps to automate common tasks and accelerate algorithm exploration.
- Accelerate algorithms on NVIDIA® GPUs, cloud, and datacenter resources without specialized programming or IT knowledge.
- Deploy algorithms to embedded devices, including NVIDIA GPUs, Intel® processors and FPGAs, and ARM-based embedded processors.
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Control Design
Power electronics engineers use MATLAB and Simulink to develop digital control systems for motors, power converters, and battery systems. MATLAB and Simulink offer:
- A multi-domain block diagram environment for modeling plant dynamics, designing control algorithms, and running closed-loop simulations
- Plant modeling using system identification or physical modeling tools
- Root locus, Bode diagrams, LQR, LQG, robust control, model predictive control, and other design and analysis techniques
- Capabilities to verify control algorithms in closed-loop desktop simulations, and then deploy them to production microcontrollers and FPGAs by automatically generating C or HDL code
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