**What is Matlab?**

MATLAB is used for a wide range of applications, in industries and academics, including machine learning and deep learning, signal processing and communications, test and measurement, image and video processing, control systems, computational finance, and computational biology by** **millions of engineers and scientists worldwide.Matlab program and script files always save by giving filenames ending with ".m" extension such as ‘program.m’.

The full form of MATLAB is Matrix Laboratory. It is a programming language developed by MathWorks which operates as a communal programming circumstances.

It is mainly used as a matrix programming language where linear algebra programming was easy and simple. It can be use both under interactive sessions and as a bunch job.

MATLAB is used for scientific and technical computing, it is a high-performance language. MATLAB allow students to give fluidity in MATLAB programming language. It collaborates computation,calculation, visualization, and programming in an easy-to-use and simple domain where problems and solutions are show in recognizable mathematical symbols. Problem-oriented MATLAB samples have been expressed in simple and easy way to build your learning fast and successful.

It permits matrix manipulations; develop algorithms; representation of functions and data; creation of user interactions; implementation of algorithms; interfacing with programs written in other languages, such as C, C++, Java, and FORTRAN; analyze data; and create models and applications.

MATLAB contains a large variety of predefined commands and math functions that assist you in mathematical calculations, solving numerical problems and generating models.

MATLAB is acclimated in every part of computational mathematics.

Several widely used mathematical calculations exactly where it's utilized i.e

- Handling with Matrices and Arrays
- Transforms
- 2-D and 3-D Modelling and graphics
- Algebraic Equations
- Non-linear Features
- Statistics
- Linear Algebra
- Integration
- Data Evaluation
- Calculus as well as Differential Equations
- Numerical Calculations
- Curve Fitting
- Various additional unique features

- Math and computation
- Computational Finance
- Image and Video Processing
- Algorithm development
- Computational Biology

**Features of MATLAB:**

- MATLAB is a high-level programming language which Supports Object oriented programming.
- Communal graphics: MATLAB has built-in or predefined graphics to increase user experience.
- It gives the facility to functions for combining MATLAB oriented algorithms with other languages such as Java, C, .NET and MS Excel etc.
- A vast library of Mathematical functions: MATLAB consists of a large built-in library of functions needed for mathematical analysis of any information.
- It also provides an interactive environment for constant investigation, design and problem solving.

**Drawbacks or disadvantages of MATLAB:**

MATLAB usually takes more time to execute as compared to compiled languages for example, C, C++ because it is an interpreted or explicit language . It really is expensive as compared to regular C or Fortran compiler. While there is no "free" versions of Matlab is available on the internet, there is a certified license, which works until this date. After this date,it will be expired. It is expensive to purchase for Individuals.

There is no free version of MATLAB is available for students also.

It requires fast computer with large amount of memory.

**There are some basic difference between matlab and C are: -**

Matlab | C |

- Untyped language (no need to declare variable data type and size before using them) - Built -in defination of matrix data type - Built-in complex variable data type - Change in variable size allowed without programming - Extensive support for linear algebra and application-specific libraries organized in toolboxes - Rich built-in visualization | - Strictly typed language (must declare variable data type and size before using them) - No build-in definition of a matrix data type - No complex variable data type - Changes in variable size allowed explicitly through dynamic memory allocation - No support for linear algebra and application specific libraries |

**Matlab - array calculation: -**

Operation | Symbol | Example |

Addition, ( x + y ) | ‘+’ | ( X + Y ) |

Subtraction, ( x – y ) | ‘-‘ | ( X – Y ) |

Multiplication, ( x * y ) | ‘*’ | ( X * Y ) |

Division, ( x / y ) | ‘/ or inv()’ | ( X / Y ) = X * inv( Y ) |

Exponentiation, ( x^{T }) | ‘ | X’ |

**Matlab – scalar and array operation:**

Element by element operation | Representative data x = [ x _{1}, x_{2}, … , x_{n}], y = [y_{1}, y_{2}, [ ], y_{n }], z = ( <x scalar> ) |

Scalar addition | x + z = [ (x_{1} + z), (x_{2} + z), …., (x_{n }* z) ] |

Addition of array | x + y = [ (x_{1} + y_{1)}, (x_{2} + y_{2}), ….., (x_{n }+ y_{n}) ] |

Multiplication of array | x * y = [ (x_{1 }* y_{1}), ( x_{2 }* y_{2}), …., ( x_{n }* y_{n}) ] |

Division of array | x / y = [ (x_{1} / y_{1}), (x_{2} / y_{2}) , …., (x_{n} / y_{n}) ] |

Exponentiation of array | x ^ z = [ (x _{1} ^ z), (x_{2 }^ z), …., (x_{n} ^ z)]z ^ x = [ (z ^ x _{1}), (z ^ x_{2}), …., (z ^ x_{n})]x ^ y = [ (x _{1 }^ y_{1}), (x_{2} ^ y_{2}), …., (x_{n} ^ y_{n})] |

**Array addressing: -**

Array addressing | Description |

A ( r, z ) | Indicates the elements by the r^{th }row and the z^{th }column |

A ( r, : ) | Addresses the subarray just A described through the index vector associated with preferred rows in r as well as all columns |

A ( :, z ) | Addresses the subarray just A described through all rows as well as the index vector associated with preferred columns in z |

A ( x : y, z : u) | Addresses a subarray within A intersected by the rows from x to y and the column from z to u |

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