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Coefficient and Augmented Matrix
Augmented is like coefficient but with coefficients to right of equal sign too.
Row echelon form
All zero rows are at bottom
In each non-zero row, each leading entry is in a column to the left of any leading entries below it.
Reducing to REF is called Guassian elimination.
Elementary row operations
Only do one ERO at a time.
Multiply rows by constant
Swapping rows
Adding or subtracting rows from each other
Parameter variables
Used when first non-zero row has two coefficients, so infinite many solutions.
eg. 2x + 3y = 4 → x = 2 - (3a) / 2, (swap y with a)
No real solutions
Zero row equal to zero.
Reduced row echelon form
Is in REF
Every non-zero row’s leading entry is an 1 and there are no other non-zero entries in the leading entry’s column.
Reducing to RREF is called Gauss-Jordan elimination.
Diagonal & scalar matrix
Diagonal matrix is square matrix in which all non-diagonal entries are 0.
Scalar matrix is diagonal matrix where all diagonal entries are equal to each other, but not 0.
Upper and lower triangular matrix
Square matrix where all entries below/above diagonal are zero (opposite to it’s name).
n x n Identity matrix
Square matrix with dimension n.
All non-diagonal entries are zero and diagonal entries are 1.
Mathematically equal to 1.
Equal matrices and zero matrices
Same size and all entries equal.
Zero matrix has only zero entries.
Matrix addition/subtraction and scalar multiplication
Can add matrices if same size arithmetically.
For subtraction use A - B = A + (-1)B
Multiply each entry by scalar.
Matrix multiplication
Dot multiply row of first matrix with column of second matrix, then add individual products.
Order matters.
Transpose matrix and symmetric
AT : Rotate A clockwise 90o, then mirror horizontally.
Symmetric when A = AT
Transpose rules
(A + B)T = AT + BT
(AT)T = A
(AB)T = BTAT
(kA)T = kAT
(Ar)T = (AT)r
For every square matrix A, A + AT is symmetric.
For any matrix A, AAT and ATA are symmetric.