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Matrix of order m by n: A Matrix is a rectangular array of m × n numbers, which may be either real or complex. These numbers are set in the form of m horizontal lines and n vertical lines and altogether defined as a matrix of order m by n, and also it is represented as m × n Matrix’. The rectangular array is enclosed in either () or [] brackets.
Read the article below to learn more about the Matrices.
Types of Matrices
There are different types of Matrices. The divisions in the matrices are done based on the number of elements, the number of rows and columns or their order. Different matrices on the basis of the factors mentioned above are:
Type of Matrix  Details 
Row Matrix  A = [a_{ij}]_{1×n} 
Column Matrix  A = [a_{ij}]_{m×1} 
Zero or Null Matrix  A = [a_{ij}]_{mxn,} where, a_{ij} = 0 
Singleton Matrix  A = [a_{ij}]_{mxn} where, m = n =1 
Horizontal Matrix  [a_{ij}]_{mxn} where n > m 
Vertical Matrix  
Square Matrix  [a_{ij}]_{mxn} where, m = n 
Diagonal Matrix  A = [a_{ij}] when i ≠ j 
Scalar Matrix  A = [a_{ij}]_{mxn} [a_{ij}] = k when i = j [a_{ij}] = 0 when i ≠ j 
Identity (Unit) Matrix  A = [a_{ij}]_{mxn} where, [a_{ij}] = 1 when i = j [a_{ij}] = 0 when i ≠ j 
Equal Matrix  A = [a_{ij}]_{mxn} and B = [b_{ij}]_{rxs} where, a_{ij} = _{bij, m = r, and n = s} 
Triangular Matrices  Can be either upper triangular (a_{ij} = 0, when i > j) or lower triangular (a_{ij} = 0 when i < j) 
Singular Matrix  A = 0 
NonSingular Matrix  A ≠ 0 
Symmetric Matrices  A = [a_{ij}] where, a_{ij} = a_{ji} 
SkewSymmetric Matrices  A = [a_{ij}] where, a_{ij} = a_{ji} 
Hermitian Matrix  A = A^{θ} 
Skew – Hermitian Matrix  A^{θ} = A 
Orthogonal Matrix  A A^{T} = In = AT A 
Idempotent Matrix  A^{2} = A 
Involuntary Matrix  A^{2} = I, A^{1} = A 
Nilpotent Matrix  ∃ p ∈ N such that A^{P} = 0 
Matrix Operations
Matrix operations precisely involve three algebraic operations. These Matrix operations are the addition of matrices, subtraction of matrices and multiplication of matrices. Matrix is a rectangular array of different numbers of rows and columns.
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Conditions to apply operations on Matrices
To apply additional and subtraction operations on matrices, the order of all the matrices involved must be identical.
To apply multiplication operations on two matrices, the number of columns in Matrix A must equal the number of rows in Matrix B.
Addition of Matrices
If A and B are Matrices of the same order, then their sum A + B is a matrix. In the Additional Operation of two matrices, each element of the newly formed matrix is the sum of the corresponding element.
Subtraction of Matrices
If A and B are Matrices of the same order, then their difference A – B is a matrix. In the Subtraction Operation of two matrices, each element of the newly formed matrix is difference from the corresponding element.
Scalar Multiplication of Matrices
If A is a matrix and k any scalar number, then the matrix which is obtained by multiplying the elements of A by k is called the ‘scalar multiplication of A by k’ matrix. The newly formed matrix is denoted by k A.
Thus,
If, A = [a_{ij}]_{m×n}
Then, kA = [k.a_{ij}]_{m×n}
Multiplication of Matrices
If A and B are any two matrices, then their product AB will be defined only if the number of columns in the A matrix is equal to the number of rows in matrix B.
Application of Matrices
Matrices are a fundamental mathematical tool with various applications in various fields. They are used to organise and manipulate data in a structured manner, making complex calculations and analyses more manageable. Here are some key applications of matrices:

Linear Transformations
Matrices are extensively used to represent and analyse linear transformations in computer graphics, physics, and engineering. By applying matrix operations to vectors, transformations such as scaling, rotation, translation, and shearing can be easily performed.

Computer Graphics
Matrices play a crucial role in computer graphics, representing objects’ position, orientation, and projection in a 3D space. By applying matrix transformations, 3D objects can be rendered and manipulated on a 2D screen, enabling the creation of realistic graphics in video games, virtual reality, and animation.

Cryptography
Matrices are employed in encryption algorithms to secure data transmission and protect sensitive information. Techniques like the Hill cypher and the RSA algorithm use matrices to perform mathematical operations on plaintext and ciphertext, ensuring the confidentiality and integrity of data.

Markov Chains
Matrices are employed to study stochastic processes, specifically in analysing Markov chains. A Markov chain represents a sequence of events where the probability of transitioning from one state to another depends only on the current state. Matrices help in analysing the longterm behaviour and steadystate probabilities of such systems.

Optimization Problems
Matrices find extensive application in optimisation problems across various disciplines, including operations research, economics, and engineering. Linear programming, for example, involves optimising a linear objective function subject to linear constraints, which can be effectively represented and solved using matrix algebra.

Data Analysis
Matrices are utilised in data analysis and machine learning tasks. In data science, matrices represent datasets, with each row corresponding to an observation and each column representing a variable.

Electrical Circuits
Matrices are utilised in electrical circuit analysis to solve systems of linear equations that describe the behaviour of circuits. Constructing a matrix equation from circuit elements and applying techniques such as Gaussian elimination can determine circuit parameters such as current and voltage.

Structural Analysis
Matrices are crucial in structural engineering to analyse and design structures like buildings and bridges. The stiffness and flexibility matrices help determine the response of a structure to various loads and boundary conditions, facilitating the calculation of displacements, stresses, and natural frequencies.
Frequently Asked Questions on Matrices
What is a matrix?
A matrix is a rectangular array of real or complex numbers arranged in rows and columns. It is denoted by enclosing the array in parentheses or brackets.
What are the types of matrices?
There are several types of matrices, including row matrix, column matrix, zero matrix, singleton matrix, horizontal matrix, vertical matrix, square matrix, diagonal matrix, scalar matrix, identity matrix, equal matrix, triangular matrices, singular matrix, nonsingular matrix, symmetric matrix, skewsymmetric matrix, Hermitian matrix, skewHermitian matrix, orthogonal matrix, idempotent matrix, involutory matrix, and nilpotent matrix.
What are the basic operations on matrices?
The basic operations on matrices are addition, subtraction, scalar multiplication, and multiplication.
What are the conditions for matrix addition and subtraction?
To add or subtract matrices, the matrices must have the same order, which means they must have the same number of rows and columns.