Other Applications

Deep Learning

MATLAB® is an ideal platform for Machine Learning and Deep Learning

Firstly, MATLAB follows the mental process Engineers and Scientists use and allows for the incorporation of Deep Learning and Machine Learning across an entire design workflow. Secondly, Gartner classified MathWorks as a leader in the domain of Data Science in 2020. While other platforms focus on the development of algorithms, MATLAB understands that algorithms will be used in the development of a product or service that will be launched on the market.

Across the Aerospace and Defense, Automotive and Automation & Robotic industries, Deep Learning is being applied in Automated Driving, Radar and Predictive Maintenance

Similarly, MATLAB is being used for Deep Learning applications within the Energy Production, Mining and Materials and Geographical Sciences for Image Processing & labelling, Energy Forecasting, Predictive Maintenance & Infrastructure Management

In the Medical Devices industry, Scientists are using Deep Learning models with image processing & computer vision for Tumour detection, Artificial Speech, Creating Safer Machines and Diagnosis with Augmented Reality

MATLAB & Simulink

FPGA, SoC And ASIC

Develop prototype and production applications for deployment on FPGA, ASIC, and SoC devices

Use Simulink® to model and simulate digital, analog, and software together at a high level of abstraction
Convert to fixed-point using automated guidance, or generate native floating-point operations for any target device
Analyze hardware and software architectures by modeling memories, buses, and I/Os
Generate optimized, readable, and traceable VHDL® or Verilog® for implementation in digital logic
Generate processor-optimized C/C++ code to target embedded processors
Verify your algorithm running in an HDL simulator or on an FPGA or SoC device connected to your MATLAB or Simulink test bench

MATLAB and Simulink products can be used for applications such as AC motor control, software-defined radio, and embedded vision.

Wireless Communications

Reduce development time, eliminate design problems and streamline testing and verification

With MATLAB, you can:

Prove algorithm and system design concepts with simulation and over-the-air signals
Generate customizable waveforms to verify conformance to the latest 5G, LTE, and WLAN standards
Create models using digital, RF, and antenna elements to explore and optimize system behavior
Automatically generate HDL or C code for prototyping and implementation without hand-coding
Create reusable golden reference models for iterative verification of wireless designs, prototypes, and implementations
Automate analysis of large-scale field test data and visualize your simulation results.

Predictive Maintenance

Develop & deploy condition monitoring and predictive maintenance software to your enterprise IT & OT systems

  • Access streaming and archived data using built-in interfaces to cloud storage, relational and nonrelational databases, and protocols such as REST, MQTT, and OPC UA.
  • Preprocess data and extract features to monitor equipment health using apps for signal processing and statistical techniques.
  • Develop machine learning models to isolate root cause of failures and predict time-to-failure and remaining useful life (RUL).
  • Deploy algorithms and models to your choice of in-operation systems such as embedded systems, edge devices, and the cloud by automatically generating C/C++, Python, HDL, PLC, GPU , .NET, or Java® based software components.
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