Vocab Flashcards

(61 cards)

1
Q

linear equation

A

an equation that can be written in the form a1x1 + … + anxn = b with b and the coefficients a1…an are real/complex numbers

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

system of linear equations/ linear system

A

collection of one or more linear equations involving the same variables

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

linear systems are equivalent if

A

they have the same solution set

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
4
Q

two matrices are row equivalent

A

if there is a sequence of elementary row operations that transforms one matrix to another

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
5
Q

leading entry

A

the leftmost nonzero number in a nonzero row

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

basic variables

A

variables that correspond to pivot columns

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
7
Q

vector / column vector

A

matrix with only one column

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

two vectors are equal if

A

their corresponding entries are equal

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

linear combination

A

y = c1v1 + … + cnvn given vectors v1,…,vn, and scalars c1,…,cn

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
10
Q

homogeneous

A

Ax=0

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
11
Q

trivial solution

A
  • when x=0

- every homogeneous equation has the trivial solution

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
12
Q

nontrivial solution

A
  • x is nonzero

- occurs when there is a free variable

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
13
Q

linearly independent

A

set of vectors {v1, … , vp} with the vector equation x1v1+ … + xpvp = 0 with only the trivial solution

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
14
Q

linearly dependent

A

there exists weights c1, …, cp not all zeros such that c1v1 + …+ cpvp = 0

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
15
Q

transformation / function / mapping

A

a rule that assigns each vector x in Rn a vector T(x) in Rm

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
16
Q

Rn

A

domain

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
17
Q

Rm

A

codomain

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
18
Q

T(x)

A

image

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
19
Q

range

A

set of all T(x)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
20
Q

a transformation is linear if

A
T(0) = 0
T(u+v) = T(u) + T(v)
T(cu) = cT(u)
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
21
Q

onto

A

each b in Rm is the image of at least one x in Rn

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
22
Q

one-to-one

A

each b in Rm is the image of at most one x in Rn

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
23
Q

two matrices are equal if

A

they have the same size (same number of rows and columns)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
24
Q

nonsingular matrix

A

invertible matrix

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
25
elementary matrices
obtained by performing one elementary row operation on the identity matrix
26
subspace
1. includes the zero vector 2. is closed under vector addition 3. is closed under scalar multiplication
27
isomorphism from V onto W
one-to-one transformation from a vector space V onto vector space W
28
dim V
number of vectors in a basis for V
29
Row A (row space)
set of all linear combinations of the row vectors
30
rank
dimension of column space of A
31
nullity
dimension of null space
32
probability vector
vector with nonnegative entries that add up to 1
33
stochastic matrix
square matrix whose columns are probability vectors
34
steady-state vector / equilibrium vector
probability vector q such that Pq=q
35
stochastic matrix is regular if
some matrix power P^k contains only positive entries
36
eigenvector
NONZERO vector x such that Ax=(lambda)x
37
eigenspace
set of all solutions of (A-(lambda)I)x=0
38
characteristic equation
det(A-(lambda)I)=0
39
multiplicity
number of times it appears as a root of the characteristic equation
40
two matrices A and B are similar if
there is an invertible matrix such that A=PBP^-1
41
diagonalizable
matrix A is similar to a diagonal matrix
42
if all eigenvalues are greater than 1, the origin is a
repeller
43
if all eigenvalues are less than 1, the origin is a
attractor
44
if some eigenvalues >1 and others <1, the origin is a
saddle point
45
for complex eigenvalues, if absolute value of eigenvalue > 1
spiral away from origin
46
for complex eigenvalues, if absolute value of eigenvalue < 1
spiral toward origin
47
``` if Re (lambda) > 0 ** differential equations ```
trajectories spiral outward
48
if Re (lambda) = 0
trajectories form ellipses
49
unit vector
vector whose length is 1
50
two vectors are orthogonal if
their dot product is 0
51
orthogonal complement
set of all vectors z that are orthogonal to every vector in subspace W
52
orthonormal set
orthogonal set of unit vectors
53
symmetric matrix
matrix such that the transpose of A = A
54
orthogonal matrix
inverse of P = transpose of P; orthonormal columns
55
spectrum
set of eigenvalues of a matrix
56
positive definite
Q(x) > 0 for all x =/= 0
57
negative definite
Q(x) < 0 for all x =/= 0
58
indefinite
Q(x) <0 and >0 for all x =/= 0
59
positive semidefinite
Q(x) >= 0 for all x
60
negative semidefinite
Q(x) <= 0 for all x
61
singular values of A
square roots of the eigenvalues of A