Most Essential Application of Matlab Programming

MATLAB can be used to simulate various electrical networks, but recent advancements in MATLAB have made it a very competitive tool for Artificial Intelligence, Robotics, Image processing, Wireless communication, Machine learning, Data analytics, and other applications. Though it is mostly used in the engineering domain by circuit branches and mechanical to solve a basic set of problems, its application is vast. It is a programme that allows you to compute, programme, and graphically visualise the results.

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What is Matlab?

Matlab is a programming language that is similar to other well-known languages such as Java, C#, and others, and it comes with its own IDE (Integrated Development Environment) and library set. Matlab is an abbreviation for “Matrix Laboratory,” as it was originally known as the matrix programming language. It is a programming language of the fourth generation. Cleve Moler, the Chairman of the Computer Science department at the University of New Mexico at the time, was the first to discover it. His goal was to find a way for his students to perform linear algebra and numerical computations without having to use Fortran. MathWorks was founded in 1984 by Cleve Molar, Steve Bangart, and Jack Little, who recognised Matlab’s commercial potential.

Application of Matlab Programming 

Here are a few MATLAB applications:

Statistics and machine learning(ML)

This MATLAB toolbox can be very useful for programmers. Statistical methods such as descriptive or inferential statistics are simple to implement. The same is true for machine learning. To solve modern-day problems, various models can be used. The algorithms used are also applicable to big data applications.

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Curve fitting

The curve fitting toolbox aids in the analysis of data occurrence patterns. After obtaining a specific trend, which can be a curve or a surface, future trends can be predicted. Plotting, calculating integrals, derivatives, interpolation, and other functions are available.

Control systems

The nature of systems can be obtained. Closed-loop, open-loop, controllability and observability, Bode plot, Nyquist plot, and other factors can be obtained. Control techniques like PD, PI, and PID can be visualised. Analysis can be performed in either the time domain or the frequency domain.

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Signal Processing

Signals and systems, as well as digital signal processing, are taught in a variety of engineering programmes. However, MATLAB allows for proper visualisation of this. On any given signal, various transforms such as Laplace, Z, and so on can be performed. Validation of theorems is possible. Analysis can be performed in either the time domain or the frequency domain. There are numerous built-in functions available.

Mapping

Mapping has numerous applications in a variety of fields. For example, in big data, the MapReduce tool is very important, and it has many real-world applications. Data mapping can be used for theft analysis or financial fraud detection, regression models, contingency analysis, predicting techniques in social media, data monitoring, and so on.

Deep learning

It is a machine learning subclass that can be used for speech recognition, financial fraud detection, and medical image analysis. Time-series, Artificial neural networks (ANN), Fuzzy logic, or a combination of these tools can be used.

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Financial analysis

Before embarking on any venture, an entrepreneur must conduct a thorough survey and financial analysis to determine the best course of action. All of the tools required for this are available in MATLAB. Profitability, solvency, liquidity, and stability can all be identified. Business valuation, capital budgeting, cost of capital, and other factors can be assessed.