Operations with matrices (addition, subtraction, scalar multiplication)
Operations with matrices (addition, subtraction, scalar multiplication)
Understanding Matrices
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A matrix is a rectangular array of numbers arranged in rows and columns. It is a useful mathematical tool in dealing with grouped data.
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The size of a matrix is determined by its number of rows and columns, expressed as
r x c
, wherer
indicates the number of rows, andc
shows the number of columns. -
The position of an element in a matrix is defined by its row and column number.
Matrix Operations
Addition & Subtraction
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Two matrices can only be added or subtracted if they are of the same size.
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Matrix addition or subtraction is performed element-by-element. That is, to add or subtract two matrices, simply add or subtract the corresponding elements.
Scalar Multiplication
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Scalar multiplication involves multiplying a matrix by a scalar (a single numeric value).
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Each element in the matrix is multiplied by the scalar.
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This operation can be applied to matrices of any size.
Performing Matrix Operations
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When adding or subtracting matrices, ensure they have the same dimensions. Then add or subtract the corresponding elements individually.
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For scalar multiplication, you multiply every element in the matrix by the scalar to generate a new matrix.
Understanding Matrices Operations
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The order of matrix addition or subtraction does not matter. That is,
A + B = B + A
andA - B ≠ B - A
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Scalar multiplication is also commutative as follows:
λ(A+B) = λA + λB
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Basic operations with matrices form the fundamentals for more complex matrix operations such as multiplication of matrices and finding inverse of a matrix.
Applications of Matrix Operations
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Matrix operations are widely used in programming, physics, engineering and computer graphics for tasks such as transformation and manipulation of data.
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Knowledge of matrix operations can prove useful in solving systems of linear equations in multiple variables.
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Also, understanding matrix operations can ease the understanding of advanced topics like eigenvectors and eigenvalues.