Cub11k's BIU Notes
Cub11k's BIU Notes
Assignments
Discrete-math
Discrete-math 1
Discrete-math 10
Discrete-math 11
Discrete-math 12
Discrete-math 2
Discrete-math 3
Discrete-math 4
Discrete-math 5
Discrete-math 6
Discrete-math 7
Discrete-math 8
Discrete-math 9
Infi-1
Infi-1 10
Infi-1 11
Infi-1 2
Infi-1 3
Infi-1 4
Infi-1 5
Infi-1 6
Infi-1 7
Infi-1 8
Infi-1 9
Linear-1
Linear-1 1
Linear-1 10
Linear-1 11
Linear-1 12
Linear-1 2
Linear-1 3
Linear-1 4
Linear-1 5
Linear-1 6
Linear-1 7
Linear-1 8
Linear-1 9
Linear-2
Linear-2 1
Lectures
Data-structures
Data-structures 1
Data-structures 2
Data-structures 3
Discrete-math
Discrete-math 10
Discrete-math 11
Discrete-math 12
Discrete-math 13
Discrete-math 14
Discrete-math 15
Discrete-math 16
Discrete-math 18
Discrete-math 19
Discrete-math 20
Discrete-math 21
Discrete-math 22
Discrete-math 23
Discrete-math 24
Discrete-math 25
Discrete-math 26
Discrete-math 3
Discrete-math 4
Discrete-math 5
Discrete-math 6
Discrete-math 7
Discrete-math 8
Discrete-math 9
Exam 2023 (2A)
Exam 2023 (2B)
Exam 2023 (A)
Exam 2023 (B)
Exam 2023 (C)
Exam 2024 (A)
Exam 2024 (B)
Exam 2024 (C)
Midterm
Infi-1
Exam 2022B (A)
Exam 2022B (B)
Exam 2023B (A)
Exam 2023B (B)
Exam 2024 (A)
Exam 2024 (B)
Exam 2025 (A)
Infi-1 10
Infi-1 12
Infi-1 13
Infi-1 14
Infi-1 15
Infi-1 16
Infi-1 17
Infi-1 19
Infi-1 20
Infi-1 21
Infi-1 22
Infi-1 23
Infi-1 24
Infi-1 25
Infi-1 26
Infi-1 5
Infi-1 6
Infi-1 7
Infi-1 9
Midterm
Theorems and proofs
Infi-2
Infi-2 1
Infi-2 10
Infi-2 11
Infi-2 12
Infi-2 13
Infi-2 14
Infi-2 15
Infi-2 16
Infi-2 17
Infi-2 2-3
Infi-2 3-4
Infi-2 5
Infi-2 6
Infi-2 7
Infi-2 8
Infi-2 9
Linear-1
Exam 2023 (B)
Exam 2023 (C)
Exam 2024 (A)
Exam 2024 (B)
Exam 2024 (C)
Exam 2025 (A)
Linear-1 11
Linear-1 12
Linear-1 13
Linear-1 4
Linear-1 5
Linear-1 6
Linear-1 7
Linear-1 8
Linear-1 9
Midterm
Random exams
Theorems and proofs
Linear-2
Linear-2 1
Linear-2 2
Linear-2 3
Linear-2 4
Linear-2 5
Linear-2 6
Linear-2 7
Linear-2 8
Seminars
CSI
CSI 2
Data-structures
Data-structures 1
Data-structures 2
Data-structures 3
Discrete-math
Discrete-math 1
Discrete-math 10
Discrete-math 11
Discrete-math 12
Discrete-math 2
Discrete-math 3
Discrete-math 4
Discrete-math 5
Discrete-math 6
Discrete-math 7
Discrete-math 8
Discrete-math 9
Infi-1
Infi-1 10
Infi-1 11
Infi-1 12
Infi-1 13
Infi-1 3
Infi-1 4
Infi-1 5
Infi-1 6
Infi-1 8
Infi-2
Infi-2 1
Infi-2 2
Infi-2 3
Infi-2 4
Infi-2 6
Infi-2 7
Infi-2 8
Linear-1
Linear-1 10
Linear-1 11
Linear-1 12
Linear-1 3
Linear-1 5
Linear-1 6
Linear-1 7
Linear-1 8
Linear-1 9
Linear-2
Linear-2 1
Linear-2 2
Linear-2 3
Linear-2 4
Linear-2 5
Linear-2 6
Linear-2 7
Templates
Lecture Template
Seminar Template
Home
Linear-1 6
Linear-1 6
V
is a vector space
U
,
W
are vector subspaces of
V
U
∩
W
is a vector subspace of
V
Proved on lectures
Exercise
V
=
R
2
[
x
]
U
=
{
p
(
x
)
∈
V
|
p
(
2
)
=
0
}
W
=
{
p
(
x
)
∈
V
|
p
(
x
)
=
x
p
′
(
x
)
}
Show:
U
∩
W
is a vector subspace
Solution:
U
=
{
a
0
+
a
1
x
+
a
2
x
2
|
a
0
+
2
a
1
+
4
a
2
=
0
}
W
=
{
a
0
+
a
1
x
+
a
2
x
2
|
a
0
+
a
1
x
+
a
2
2
=
x
(
a
1
+
2
a
2
x
)
=
a
1
x
+
2
a
2
x
2
}
=
=
{
a
0
+
a
1
x
+
a
2
x
2
|
a
0
−
a
2
x
2
=
0
}
=
{
a
0
+
a
1
x
+
a
2
x
2
|
a
0
=
0
a
2
=
0
}
U
∩
W
=
{
a
0
+
a
1
x
+
a
2
x
2
|
a
0
=
0
a
2
=
0
a
1
=
0
}
=
{
0
}
⟹
U
∩
W
is a vector subspace of
V
V
is a vector space
U
,
W
are vector subspaces of
V
U
+
W
=
{
u
+
w
|
u
∈
U
,
w
∈
W
}
is a vector subspace of
V
Proved in lectures
Exercise
V
=
R
n
×
n
U
=
{
A
∈
V
|
A
=
A
T
}
W
=
{
A
∈
V
|
A
is a diagonal matrix
}
Show:
U
+
W
is a vector subspace of
V
Solution:
W
⊆
U
⟹
U
+
W
=
U
⟹
U
+
W
is a vector subspace of
V
Exercise
V
=
R
2
×
2
U
=
{
A
∈
V
|
A
=
A
T
}
W
=
{
A
∈
V
|
A
is an upper-triangle matrix
}
Show:
U
+
W
=
V
Solution:
(
a
b
c
d
)
=
(
1
c
c
1
)
+
(
a
−
1
b
−
c
0
d
−
1
)
∀
A
∈
V
:
A
=
U
1
+
W
1
∈
U
+
W
⟹
V
⊆
U
+
W
⟹
U
+
W
is a vector subspace of
V
U
+
W
=
V
V
is a vector space
U
,
W
are vector subspaces of
V
U
⊕
W
=
V
⟺
U
+
W
=
V
∧
U
∩
W
=
{
0
}
Proved in lectures
Exercise
V
=
R
2
×
2
U
=
{
A
∈
V
|
A
=
α
I
}
W
=
{
A
∈
V
|
t
r
(
A
)
=
0
}
Show:
U
⊕
W
=
V
Solution:
Let
A
∈
V
A
=
(
a
b
c
d
)
=
(
a
+
d
2
0
0
a
+
d
2
)
⏟
=
a
+
d
2
⋅
I
+
(
a
−
d
2
b
c
d
−
a
2
)
∀
A
∈
V
:
A
=
U
1
+
W
1
⟹
V
⊆
U
+
W
⟹
V
=
U
+
W
U
∩
W
=
{
A
∈
V
|
A
=
α
I
∧
t
r
(
A
)
=
0
}
=
{
0
}
⟹
V
=
U
⊕
W
V
is a vector space over
F
,
S
⊆
V
S
=
{
v
1
,
v
2
,
…
,
v
n
}
Linear combination of
S
is a sum:
α
1
v
1
+
α
2
v
2
+
⋯
+
α
n
v
n
Sometimes denoted as:
(
S
,
{
α
1
,
α
2
,
…
,
α
n
}
)
s
p
(
S
)
is called span of
S
and is a set of all linear combinations of
S
s
p
(
S
)
=
{
α
1
v
1
+
⋯
+
α
n
v
n
|
α
1
,
α
2
,
…
,
α
n
∈
F
v
1
,
v
2
,
…
,
v
n
∈
S
}
Exercise
V
=
R
n
×
n
Define:
s
p
(
S
=
{
(
−
1
0
0
0
)
,
(
0
2
0
0
)
,
(
0
0
0
−
4
)
}
)
Solution:
s
p
(
S
)
=
{
(
−
α
2
β
0
−
4
γ
)
|
α
,
β
,
γ
∈
R
}
Exercise
V
=
R
2
[
x
]
8
−
3
x
+
x
2
∈
?
s
p
(
S
=
{
1
+
x
2
,
x
+
x
2
,
3
+
x
+
2
x
2
}
)
Solution:
{
α
+
3
γ
=
8
β
+
γ
=
−
3
α
+
β
+
2
γ
=
1
⟺
{
α
+
3
γ
=
8
β
+
γ
=
−
3
β
−
γ
=
−
7
⟺
{
α
+
3
γ
=
8
β
+
γ
=
−
3
−
2
γ
=
−
4
⟺
{
α
=
2
β
=
−
5
γ
=
2
(
v
1
v
2
v
3
p
1
1
0
3
8
x
0
1
1
−
3
x
2
1
1
2
1
)
⟹
8
−
3
x
+
x
2
∈
s
p
(
S
)
Exercise
V
=
R
3
W
=
s
p
(
{
(
1
2
0
)
,
(
2
3
−
1
)
,
(
0
1
1
)
}
)
Show:
W
=
{
(
x
y
z
)
|
2
x
−
y
+
z
=
0
}
Solution:
W
=
{
(
x
y
z
)
|
∃
α
,
β
,
γ
:
α
(
1
2
0
)
+
β
(
2
3
−
1
)
+
γ
(
0
1
1
)
=
(
x
y
z
)
}
=
=
{
(
x
y
z
)
|
(
1
2
0
x
2
3
1
y
0
−
1
1
z
)
has a solution
}
=
=
{
(
x
y
z
)
|
(
1
2
0
x
0
−
1
1
y
−
2
x
0
0
0
2
x
−
y
+
z
)
has a solution
}
=
=
{
(
x
y
z
)
|
2
x
−
y
+
z
=
0
}