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preface
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Nickname: Haihong
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Introduction: because of C language to get acquainted with programming, then transferred to the computer major, had the honor to get some national awards, provincial awards… Has been confirmed. Currently learning C++/Linux/Python
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Machine learning little White stage
The article is only used as my own study notes for the establishment of knowledge system and review
Know what is, know why!
2.3 inverse matrix
define
For the n-order matrix AAA, if I have an n-order matrix BBB, such that AB equals BA equals EAB equals BA equals E
The matrix A is invertible and the matrix B is called the inverse matrix of A, or the inverse matrix for short
Keep in mind that
If A is invertible, then the inverse of A must be unique.
Proof: Suppose B and C are the inverse matrices of A, there are
It is concluded that B = C
So the inverse of A is unique.
writing
The inverse matrix of the AAA as A – 1 A ^ {1} A – 1 if AB = BA = E, the B = A – 1 AB = BA = E, the B = A ^ {1} AB = BA = E, B = A – 1
Theorem 1
content
If matrix A reversible, the ∣ A ∣ indicates 0 | | \ A neq 0 ∣ A ∣ = 0
prove
Because the matrix A is invertible, there must be A−1A^{-1}A−1, such that
launch
Theorem 2
content
If ∣ A ∣ indicates 0 | | \ A neq 0 ∣ A ∣ = 0, AAA reversible matrix, and A – 1 = 1 ∣ A ∣ A ∗ A ^ {1} = \ frac {1} {| A |} A ^ * A – 1 = ∣ A ∣ 1 A ∗, including A ∗ ∗ A ^ * A as AAA adjoint matrix
prove
Known AA ∗ = ∣ A ∣ EAA ^ * = | A | EAA ∗ = ∣ A ∣ E (| | A is A constant)
Because ∣ A ∣ indicates 0 | | \ A neq 0 ∣ A ∣ = 0
So ∣ A ∣ AA ∗ = 1 A1 ∣ A ∣ A ∗ = A (1 ∣ A ∣ A ∗) = E \ frac {1} {| |} A AA ^ * = A \ frac {1} {| A |} A ^ * = A (\ frac {1} {| A |} A ^ *) = E ∣ A ∣ 1 AA ∗ = A ∣ A ∣ 1 A ∗ = A (∣ A ∣ 1 A ∗) = E
And because A ∗ A = AA ∗ A * A = AA ^ ^ * AA ∗ ∗ A = A
So 1 ∣ ∣ A AA ∣ A ∣ A ∗ ∗ = 1 A = (1 ∣ A ∣ A ∗) A = E \ frac {1} {| |} A AA ^ * = \ frac {1} {| A |} ^ A * A = (\ frac {1} {| A |} A ^ *) ∣ A ∣ 1 AA ∗ = A = E ∣ A ∣ 1 A ∗ A = (∣ A ∣ 1 A ∗) A = E
by
We know that matrix A has an inverse matrix,
And A – 1 = 1 ∣ A ∣ A ∗ A ^ {1} = \ frac {1} {| A |} A ^ * A – 1 = ∣ ∣ A ∗ 1 A
Proof done!
inference
If AB=E (or BA=EAB=E (or BA=EAB=E (or BA=E) then B=A−1B=A^{-1}B=A−1
Proof:
Because the AB = the EAB = the EAB = E
So ∣ A ∣ ∣ B ∣ = ∣ ∣ E = 1 | | | | = | E | = 1 B ∣ A ∣ ∣ ∣ = B ∣ ∣ E = 1
So the ∣ A ∣ indicates 0 | A | \ neq0 ∣ A ∣ = 0, A – 1 A ^ {1} there – 1 A
Proof done!
Operation rule
Square matrix inverse matrix to meet operational rules (1) if the AAA reversible, then A – 1 A ^ {1} A – 1 is reversible, and (A) – 1-1 = A (A ^ {1}) ^ {1} = A (A) – 1-1 = A
Proof:
Because AAA is invertible
so
So let’s say that B is equal to AB is equal to AB is equal to A
launch
and
Proof done!
Number (2) if the AAA reversible, lambda indicates \ lambda \ lambda neq 0 0 = 0, the lambda \ lambda A lambda A reversible, and lambda (A) – 1-1 = 1 lambda A \ lambda (A) ^ {1} = \ frac {1} {\ lambda} A ^ {1} (lambda A) = 1 A lambda – 1-1
Proof:
Because AAA is invertible
so
For λA\lambda AλA
There must be 1λB\frac{1}{\lambda} Bλ1B such that
Lambda (1 B) = (lambda A) lambda (1 B) lambda (A) = E \ lambda (A) (\ frac {1} {\ lambda} B) = (\ frac {1} {\ lambda} B) = E \ lambda (A) (lambda A) (1 B) lambda = (1 B) lambda lambda (A) = E so
λA\lambda AλA is also reversible
At the same time
(3) if A, BA, BA, B for the same order matrix and are reversible, the ABABAB are reversible, and (AB) – 1 = B – A – 1 (AB) ^ {1} = B ^ A ^ {1} {1} (AB) = B – 1-1 A – 1 to prove:
Because A, BA, BA, and B are matrices of the same order and invertible
so
-
-
because
-
-
so
ABABAB reversible and (AB) – 1 = DC = B – A – 1 (AB) ^ {1} = DC = B ^ A ^ {1} {1} (AB) – 1 = DC = B – 1-1 A
Proof done!
(4) if AAA reversible, ATA ^ {T} the AT is reversible, and (AT) – 1 = (A – 1) T (A ^ {T}) ^ {1} = (A ^ {1}) ^ {T} (AT) = (A – 1) T – 1
Proof:
Because AAA is invertible
the
I take the transpose, I get
By (AB) T = BTAT (AB) ^ ^ T ^ T = B TA (AB) T = BTAT
so
ATA ^ TAT reversible
and
Proof done!
conclusion
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