Definitions [4]
Let \[A = [a_{ij}]\] be an \[m \times n\] matrix and \[B = [b_{jk}]\] be an \[n \times p\] matrix.
Then the product C = AB is an \[m \times p\] matrix \[C = [c_{ik}]\], where each entry \[c_{ik}\] is given by:
Consistent Solution: A system is consistent if it has at least one solution.
Inconsistent Solution: A system is inconsistent if it has no solution.
Two matrices are equivalent if one can be obtained from the other by a finite number of elementary operations
-
Denoted by: A ∼ B
If A = [aij], then the negative of A, denoted by −A, is the matrix obtained by replacing each element aij by −aij
−A = [−aij]
- Order of −A = order of A
Formulae [3]
Minor
Delete ith row and jth column: Mij
Cofactor of aij
Aij = (−1)i+j × (minor of aij)
Sign pattern:
\[\begin{bmatrix}
+ & - & + \\
- & + & - \\
+ & - & +
\end{bmatrix}\]
Adjoint of A = transpose of the cofactor matrix \[\mathrm{adj}A=\left[A_{ij}\right]^T\]
-
\[\mathrm{adj}(kA)=k^{n-1}\mathrm{adj}(A)\]
-
A(adj A) = (adj A)A = ∣A∣I
-
∣adjA∣ = ∣A∣n−1(for an n×n non-singular matrix)
\[A=
\begin{bmatrix}
a & b \\
c & d
\end{bmatrix}\]
\[A^{-1}=\frac{1}{ad-bc}
\begin{bmatrix}
d & -b \\
-c & a
\end{bmatrix}\] if ad − bc ≠ 0
\[A^{-1}=\frac{1}{|A|}(\operatorname{adj}A)\], if ∣A∣ ≠ 0
Properties:
-
\[(AB)^{-1}=B^{-1}A^{-1}\]
-
\[(A^{-1})^{-1}=A\]
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\[(A^{\prime})^{-1}=(A^{-1})^{\prime}\]
- If inverse exists, it is unique.
Key Points
-
Matrix multiplication is row-by-column, not term-wise.
-
Product AB exists only if columns of A = rows of B.
-
If A is \[m \times n\] and B is \[n \times p\], then AB is \[m \times p\].
-
In general, \[AB \neq BA\], and sometimes one product may not even be defined.
-
Matrix multiplication is associative and distributive over addition.
-
Identity matrix acts as a multiplicative identity: AI = IA = A.
-
Zero matrix absorbs multiplication: AO = OA = O.
Method of Inversion
- Given: AX = B
- Multiply both sides by A⁻¹
Result:
- X = A⁻¹B
Key Steps:
- Pre-multiply by A⁻¹
- Use property: A⁻¹A = I
- Final solution: X = A⁻¹B
Method of Reduction
- No need to find A⁻¹
- Apply elementary row operations to the matrix. Process:
- Convert the matrix into upper triangular form
- System reduces to:
- b₁₁x + b₁₂y + b₁₃z = b₁′
- b₂₂y + b₂₃z = b₂′
- b₃₃z = b₃′
Final Step:
- Solve using back substitution:
- First find z
- Then y
- Then x
-
An is defined only when A is a square matrix.
-
AmAn = Am+n
-
In =
| Type | Transformation | Symbol |
|---|---|---|
| Interchange | Swap two rows/columns | Ri ↔ Rj |
| Multiplication | Multiply row/column by non-zero scalar k | Ri → kRi |
| Row addition | Add k times one row to another | Ri → Ri + kRj |
-
Write AX = B
-
Apply row operations on A
(Same operations on B) -
Reduce A to triangular/identity form
-
Solve equations
Comparable Matrices
-
Two matrices are said to be comparable if they have the same order
(same number of rows and columns).
Equal Matrices
Two matrices A= [aij] and B=[bij] are equal if:
-
They are comparable (same order), and
-
Their corresponding elements are equal.
Matrix Form: AX = B
Condition:
-
A must be square
-
∣A∣ ≠ 0 (Non-singular)
Formula:
\[X=A^{-1}B\]
Important Questions [5]
- Check whether the following matrix is invertible or not: [cosθsinθ-sinθcosθ]
- If A = [x000y000z] is a non-singular matrix, then find A−1 by using elementary row transformations. Hence, find the inverse of [20001000-1]
- Find the inverse of A = cossinsincos[cosθ-sinθ0sinθcosθ0001] by elementary row transformations.
- Solve the following system of equations by the method of inversion. x – y + z = 4, 2x + y – 3z = 0, x + y + z = 2
- Solve the following system of equations by the method of reduction: x + y + z = 6, y + 3z = 11, x + z = 2y.
