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This set of vocabulary flashcards covers fundamental concepts of matrix algebra and determinants, including matrix types, special matrix forms, operations like trace and transpose, and system of equations terminology.
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Matrix
A set of m×n numbers (real or complex) arranged in the form of a rectangular array having m rows and n columns.
Singleton matrix
A matrix containing only one element, where the number of rows m and columns n are both equal to 1.
Row matrix
A matrix having only one row, also called a row vector, with a general form of order 1×n.
Column matrix
A matrix having only one column, also called a column vector, with a general form of order m×1.
Zero or Null matrix
A matrix in which all elements are equal to zero.
Horizontal matrix
A matrix of order m×n where the number of columns is greater than the number of rows (n > m).
Vertical matrix
A matrix of order m×n where the number of rows is greater than the number of columns (m > n).
Square matrix
A matrix where the number of rows is equal to the number of columns (m=n).
Conjugate elements
In a square matrix of order n×n, the elements aij and aji are referred to by this term.
Diagonal Matrix
A square matrix in which all elements are zero except those in the principal diagonal (aij=0 when i=j).
Scalar Matrix
A diagonal matrix in which all principal diagonal elements are equal to a constant value K.
Unit Matrix (Identity matrix)
A diagonal matrix in which each diagonal element is equal to unity (1), denoted as In.
Upper Triangular Matrix
A square matrix in which all elements below the principal diagonal are zero (aij=0 for all i > j).
Lower Triangular Matrix
A square matrix in which all elements above the principal diagonal are zero (aij=0 for all j > i).
Singular matrix
A square matrix whose determinant is equal to zero (∣A∣=0).
Non-singular matrix
A square matrix whose determinant is not equal to zero (∣A∣=0).
Submatrix
A matrix obtained by omitting any rows or columns of a given matrix.
Equality of Matrix
Two matrices are equal if they are of the same order and their corresponding elements are equal.
Trace of a matrix
The sum of the diagonal elements of a square matrix A, denoted as tr(A), which is ∑i=1naii.
Transpose of a matrix
The matrix obtained by interchanging the rows and columns of an original matrix A, denoted by AT or A′.
Orthogonal matrix
A square matrix A such that the product with its transpose yields the identity matrix (AAT=ATA=I).
Idempotent matrix
A square matrix A such that A2=A.
Involutory matrix
A square matrix A such that A2=I; its determinant value is always ±1.
Nilpotent matrix
A square matrix A such that Ak=0 for some positive integer k; the least such value of k is called the index.
Symmetric matrix
A square matrix A that is equal to its transpose (A=AT), meaning aij=aji for all indices.
Skew-symmetric matrix
A square matrix A such that AT=−1×A, meaning aij=−aji and all diagonal elements are zero (aii=0).
Minor
The value Mij obtained by deleting the ith row and jth column of a determinant.
Co-factor
The value of an element aij defined as Cij=(−1)i+j×Mij, where Mij is the minor.
Adjoint of a matrix
The transpose of the matrix of co-factors of the elements of a given square matrix A, denoted by adj(A).
Inverse of a Matrix
A matrix A−1 such that A×A−1=A−1×A=I, calculated as ∣A∣1×adj(A), provided ∣A∣=0.
Consistent system
A system of equations that has one or more solutions.
Inconsistent system
A system of equations that has no solution.
Trivial solution
A solution to a homogeneous system where all variables are simultaneously zero (x=y=z=0).
Characteristic Equation
The equation formed by taking the determinant of the matrix minus a scalar multiple of the identity matrix equal to zero (∣A−λI∣=0).