Updated June 23, 2023
Introduction to Matlab
Matrix Laboratory, or MATLAB for short, is a multi-paradigm numerical computing environment and proprietary programming language developed by Mathworks. It combines computation, visualization, and programming in an easily usable environment and is all expressed in mathematical equations. Written in C, C++, and Java, Matlab was initially released in 1984. The latest version was released on March 2018.
Applications of Matlab are built around the Matlab scripting language and revolve based on the following mathematical concepts:
- Variables
- Vectors and matrices
- Structures
- Functions
- Function handles
- Classes and object-oriented programming
Top Uses of Matlab
Matlab is a numerical computing environment. According to the Matlab website, the environment is designed for the following uses.
1. Embedded Systems
Embedded systems are computer systems with hardware and software components designed to do a specific task. Some examples of embedded systems are washing machines, printers, automobiles, cameras, industrial machines, etc. With the push of one button, Matlab allows us to generate code and run it on hardware.
2. Control systems
Another common reason Matlab is important is that it controls devices and systems. A control system is responsible for managing, giving commands, and regulating the behavior of other devices or systems. It is based on control loops. The devices or systems being controlled can range from simple home heaters to large industrial control systems that control the processes or the machines. The control system toolbox of Matlab provides algorithms and apps for systematically analyzing, designing, and tuning linear control systems.
3. Digital signal processing
Digital signal processing uses digital processing, such as by computers or specialized digital signal processors, to perform a range of signal processing operations. Uses of Matlab products make it easy to use signal processing techniques to analyze time series data and provide a unified workflow for developing embedded systems and streaming applications.
4. Wireless communications
Wireless communication is a broad term for connecting two devices using a wireless signal. Teams in wireless Engineering use Matlab to reduce development time, eliminate design problems early, and streamline testing and verification.
5. Image processing and computer vision
Image processing is mainly focused on processing raw images and making them ready for other tasks, such as computer vision. On the other hand, computer vision looks at images like the human eye. It involves understanding and predicting the visual output. Algorithm building is vital for image processing and computer vision. Uses of Matlab provides a comprehensive environment to analyze images and build algorithms.
6. Internet of Things
The Internet of Things is the network of devices, vehicles and home appliances, and others embedded with electronics, software, sensors, actuators, and connectivity, enabling data exchange. Uses of Matlab help in the design, prototype, and deployment of IOT applications such as predictive maintenance, operations optimization, supervisory control, etc.
7. FPGA Design and Codesign
Matlab enables hardware-software to codesign by providing C/C++ and HDL code generation with targeted support for programmable SoC devices.
8. Mechatronics
Mechatronics is the technology combining electronics and mechanical engineering. Mechatronic systems require integrating mechanical, electrical, control, and embedded software subsystems. Matlab allows you to design and simulate all this in a single environment.
9. Test and Measurement
Testing and Measurement is the process in which electronic products are subjected to various tests, from physical tests to identify any physical defects to product-level functional testing. Matlab provides tools that you need to acquire and automate tasks. Once you acquire data, you can explore it and perform live visualization and analysis.
10. Computational Biology and Computational Finance
Computational biology is the study of biological data for better understanding of biological systems and relationships. Computational finance is the computer science study of financial data and financial modeling. Matlab helps by solving ordinary differential equations that model biological behavior. Also, the Matlab computational finance suite enables you to develop quantitative applications for risk management, investment management, insurance, and econometrics.
11. Robotics
Robotics is an interdisciplinary field of science and engineering. It involves mechanical engineering, electronic engineering, and computer science to create robots or human-like machines. Robotics researchers and engineers use MATLAB to design and tune algorithms, model real-world systems, and automatically generate code – all from one software environment.
12. Data Analytics
Data Analytics is the process of studying data to gain insights. It is mainly done with the help of other software and tools. Engineering and IT are using Matlab to build Big Data Analytics Systems.
13. Predictive Maintenance
We design predictive maintenance techniques to determine the condition of in-house equipment, enabling us to figure out when maintenance has to be done. The Matlab predictive maintenance toolbox provides tools for labeling data, designing condition indicators, and estimating a machine’s remaining useful life (RUL).
14. Motor and power control
Motor control algorithms regulate speed and other performance characteristics. Matlab algorithms help with energy efficiency, precision control, and system protection. It reduces algorithm development time and cost before committing to expensive hardware testing.
15. Deep Learning
Deep learning is a broader family of machine learning. The uses of Matlab are such that with just a few simple lines of coding, one can build deep learning models without having to be an expert.
Conclusion
Matlab has a wide range of applications, as we have already seen, and is used in several industries covering –
- Automotive
- Biological Sciences
- Biotech and Pharmaceutical
- Chemicals and Petrochemical
- Communications
- Electronics
- Earth, Ocean, and Atmospheric Sciences
- Energy Production
- Financial Services
- Industrial Automation and Machinery
- Medical Devices
- Metals
- Materials and Mining
- Neuroscience
- Railway Systems
- Semiconductors
- Software and Internet
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