Matlab - Numerical Computing and Analysis


MATLAB is a multi-paradigm numerical computing environment that allows matrix manipulations, plotting of functions and data, developing and implementation algorithms, creation of user interfaces, and interfacing with programs written in other languages, including C, C++, C#, Java, Fortran and Python.

Matlab

Features and benefits of MATLAB:


  • Deploy to Enterprise Applications: MATLAB code is production ready, so you can go directly to your cloud and enterprise systems, and integrate with data sources and business systems.
  • Run on Embedded Devices: Automatically convert MATLAB algorithms to C/C++ and HDL code to run on embedded devices.
  • Integrate with Model-Based Design: MATLAB works with Simulink to support Model-Based Design, which is used for multidomain simulation, automatic code generation, and test and verification of embedded systems.


  • MATLAB allows to scale our analysis to run on clusters, GPUs and clouds with minor code changes and there is no need to rewrite the code or learn big data programming and out-of-memory techniques.
  • MATLAB can be used for variety of applications in data analytics, wireless communication, deep learning, computer vision, signal processing, robotics, control systems etc.
  • MATLAB® and Simulink® products for Aerospace and Defense:


    MATLAB® and Simulink® products for Model-Based Design and technical computing are the industry-standard tools for designing, implementing, and testing air, space, naval, and land systems. Aerospace and defense companies across the globe rely on these products in major programs, such as the Joint Strike Fighter and Mars Exploration Rover, as well as for unmanned aerial vehicles and advanced wireless systems, such as software defined radio (SDR).

    Model-Based Design with MATLAB and Simulink is a modular development approach that enables engineering teams to move from internal research and development (IRAD) to design and implementation in a single environment. Companies are using this approach to:

  • Mitigate program risk by sharing system specifications, analysis, and test data
  • Reduce costly rework through early simulation of design
  • Promote reuse by interfacing with existing tools, simulations, and legacy software
  • Leverage new technologies by moving directly from IRAD to production
  • Research emerging technologies such as cyber-physical systems