Exam 1 Flashcards
1.1 systems of linear equations
What is row equivalence in matrices?
Two matrices are row equivalent if there is a sequence of elementary row operations that transforms one matrix into the other.
1.1 systems of linear equations
If the augmented matrices of two linear systems are row equivalent, what can you say about their solution set?
The two systems have the same solution set.
1.2 row reduction and echelon forms
What three properties must a matrix satisfy to be in echelon form?
Reduced echelon form?
- All nonzero rows are above any rows of all zeros.
- Each leading entry of a row is in a column to the right of the leading entry of the row above it.
- All entries in a column below a leading entry are zeroes.
Reduced:
- The leading entry in each nonzero row is 1.
- Each leading 1 is the only nonzero entry in its column.
1.2 row reduction and echelon forms
What is consistency?
What is uniqueness?
Consistent: at least one solution exists.
Uniqueness: If a solution exists, it is the only solution.
1.2 row reduction and echelon forms
What can you say about the uniqueness of the reduced echelon form?
Each matrix is row equivalent to one and only one reduced echelon matrix.
1.2 row reduction and echelon forms
What is a pivot position in a matrix A?
A location in A that corresponds to a leading 1 in the reduced echelon form of A.
1.2 row reduction and echelon forms
What is a pivot column in a matrix A?
A pivot column is a column of A that contains a pivot position.
1.2 row reduction and echelon forms
What is a basic variable?
What is a free variable?
Basic: Described in terms of the free variable(s)
Free: We may choose any value for this variable.
1.2 row reduction and echelon forms
If a linear system is consistent, what does the echelon form of a matrix look like?
The rightmost column of the augmented matrix is not a pivot column. e.g. there is no row of the form
[0 … 0 b]
1.2 row reduction and echelon forms
If a linear system is consistent, what can you say about its solution set?
Contains either (i) a unique solution, when there are no free variables, or (ii) infinitely many solutions, when there is at least one free variable.
1.3 Vector Equations
What is the zero vector?
Vector whose entries are all 0.
e.g. np.matrix(‘0; 0; 0; 0’)
1.3 Vector Equations
What is a linear combination?
Given vectors v1, v2, …, vp in R^n and given scalars c1, c2, …, cp, the vector y defined by
y = c1v1 + c2v2 + … + cpvp
is a linear combination of v1, …, vp with weights c1, …, cp.
1.3 Vector Equations
What is the relationship between the solution sets of augmented matrices and vector equations?
A vector equation
x1a1 + x2a2 + … + xnan = b
has the same solution set as
[a1 a2 … an b]
1.3 Vector Equations
When can b be generated by a linear combination of a1, …, an?
If and only if there exists a solution to the linear system corresponding to [a1 a2 … an b]
1.3 Vector Equations
What is Span {v1, …, vp} in terms of linear combinations?
What is this called?
The set of all linear combinations of v1, …, vp.
Called the subset of R^n spanned/generated by v1, …, vp.
e.g. the set of all vectors that can be written in the form
c1v1 + c2v2 + … + cpvp
1.3 Vector Equations
How do you compute if a vector b is in Span{v1, …, vp}?
Ask whether the vector equation
x1v1 + x2v2 + … + xpvp = b
has a solution,
or equivalently, asking whether a system with the augmented matrix
[v1 … vp b] has a solution.
1.3 Vector Equations
Why must the zero vector be in Span{v1, …, vp}?
Because no matter what each vector in a linear combination is, you can have weights such that
0v1 + … + 0vp,
which will always be the zero vector.
1.4 The Matrix Equation Ax=b
If A is an mxn matrix, with columns a1, …, an, and if x is a vector in R^n, then what is the product of A and x?
The product is the linear combination of the columns of A using the corresponding entries in x as weights.
e.g. Ax = [a1 a2 … an] * np.matrix(‘x1 ; …; xn’)
= x1a1 + x2a2 + … + xnan
1.4 The Matrix Equation Ax=b
If you have the matrix equation Ax=b, what vector equation and system of linear equations does it have the same solution set as?
Ax = b
x1a1 + x2a2 + … + xnan = b, where each an is a vector and each x is a component.
[a1 a2 … an b]
1.4 The Matrix Equation Ax=b
Under what conditions does Ax=b have a solution?
if and only if b is a linear combination of the columns of A.
1.4 The Matrix Equation Ax=b
Given:
Each b in R^m, the equation Ax=b has a solution
What other statements are logically equivalent?
- For each b in R^m, the equation Ax=b has a solution
- Each b in R^m is a linear combination of the columns of A
- The columns of A span R^m
- the coefficient matrix A has a pivot position in every row.
1.4 The Matrix Equation Ax=b
If A is an mxn matrix, u and v are vectors in R^n, and c is a scalar, then what are some properties about how they multiply?
a. A(u+v) = Au + Av
b. A(cu) = c(Au)
1.5 Solution Sets of Linear Systems
When is a system of linear equations said to be homogenous?
If it can be written in the form Ax = 0.
Always has at least one solution (x=0)
1.5 Solution Sets of Linear Systems
What is the trivial solution?
x=0 (the zero vector in R^m).
