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Theorem: Absorption Law
For every pair of elements a , b B,
1. a + a · b = a
2. a · ( a + b ) = a
Proof:
(1)
abaaba 1
ba 1
1 ba
1aa
Identity
Commutativity
Distributivity
Identity
Theorem: For any a B, a + 1 = 1
(2) duality.
Theorem: Associative Law
In a Boolean algebra, each of the binary operations ( + ) and ( · ) is associative. That is, for every a , b , c B,
1. a + ( b + c ) = ( a + b ) + c
2. a · ( b · c ) = ( a · b ) · c
cbacbaA
cbcbaacbaA Distributivity
cbaaacba
acabaa
aca
a
acbaa
Commutativity
Distributivity
Distributivity
Absorption Law
Absorption Law
acaba Idempotent Law
Proof:
(1) Let
cbcbaacbaA
ccbabcbacbcba
cbabbcba
bcbab
bcbbba
bba
bab
b
bcbba
Commutativity
Distributivity
Distributivity
Idempotent Law
Absorption Law
Commutativity
Absorption Law
ccbabcbacbcba
c
Putting it all together:
cbcbaacbaA
ccbabcbaacba
cba
cba
Same transitions
· before +
Theorem 11: DeMorgan’s Law
For every pair of elements a , b B,
1. ( a + b )’ = a’ · b’
2. ( a · b )’ = a’ + b’
Proof:
(1) We first prove that (a+b) is the complement of a’·b’.
Thus, (a+b)’ = a’·b’
By the definition of the complement and its uniqueness, it suffices to show: (i) (a+b)+(a’b’) = 1 and
(ii) (a+b)(a’b’) = 0.
(2) Duality (a·b)’ = a’+b’
bbaabababa
bbaaab
bbaaab
11 ab
11
1
Distributivity
Commutativity
Associativity
a’ and b’ are the complements of a and b respectively
Theorem: For any a B, a + 1 = 1
Idempotent Law
babababa
bbaaba
bbaaab
bbaaab
bbaaab
00 ab
00
0
Commutativity
Distributivity
Commutativity
Associativity
Commutativity
a’ and b’ are the complements of a and b respectively
Theorem: For any a B, a · 0 = 0
Idempotent Law
Algebra of SetsConsider a set S.
B = all the subsets of S (denoted by P(S)).
,,SPM
“plus” set-union ∪
“times” set-intersection ∩
Additive identity element – empty set Ø
Multiplicative identity element – the set S.
Complement of X B: XSX \
Theorem: The algebra of sets is a Boolean algebra.
Proof:
By satisfying the axioms of Boolean algebra:
• B is a set of at least two elements
For every non empty set S:
→ |B| ≥ 2.
SPS ,
• Closure of (∪) and (∩) over B (functions ) . BBB
., SYX definitionby )(SPX
definitionby )(SPY
definitionby )( and SPYXSYX
definitionby )( and SPYXSYX
A1. Cummutativity of ( ∪ ) and ( ∩ ).
YxXxxYX or :
XxYxxXY or :
An element lies in the union precisely when it lies in one of the two sets X and Y. Equally an element lies in the union precisely when it lies in one of the two sets X and Y. Hence,
YX XY
XYYX
YxXxxYX and :
XxYxxXY and :
XYYX
A2. Distributivity of ( ∪ ) and ( ∩ ).
.ZYXx
Xx ZYx
ZxYx
YXx ZXx ZXYXx
ZXYXZYX
Let
and
or
If ,Yx Xx Yx YXx We have and . Hence,
If ,Zx Xx Zx ZXx We have and . Hence,
or
ZXYXZYX
This can be conducted in the same manner as ⊆.
We present an alternative way:
Definition of intersection XYX XZX and
XZXYX
Also, definition of intersection YYX
definition of union ZYY ZYYX
Similarly, ZYZX
ZYZXYX
*
**
ZYXZXYX Taking (*) and (**) we get,
ZXYXZYX
Distributivity of union over intersection can be conducted in the same manner.
ZXYXZYX
A3. Existence of additive and multiplicative identity element.
XXXSX .
XXSSXSX .
identity additive -
identity tivemultiplica - S
A4. Existence of the complement.
XSXBX \.
SXXSXSXBX \\.
XXSXSXBX \\.
Algebra of sets is Boolean algebra.All axioms are satisfied
Dual transformation - Recursive definition:Dual: expressions → expressions base: 0 → 1
1 → 0a → a , a B\{0,1}
recursion step: Let E1 and E2 be Boolean expressions. Then,
E1’ → [dual(E1)]’ ( E1 + E2 ) → [ dual(E1) · dual(E2) ]
( E1 · E2 ) → [ dual(E1) + dual(E2) ]
Boolean expression - Recursive definition: base: 0 , 1 , a B – expressions. recursion step: Let E1 and E2 be Boolean expressions. Then,
E1’ ( E1 + E2 )
( E1 · E2 )
Proof:
Let f ( x1 , x2 , … , xn ) be a Boolean expression.
We show that applying the complement on the whole expression together with replacing each variable by it’s complement, yields the dual transformation definition.
Let fd be the dual of a function f ( x1 , x2 , … , xn )
Lemma: In switching algebra, fd = f’ ( x1’ , x2’ , … , xn’ )
Induction basis: 0 , 1 – expressions.
0xf nxxxf ,,, 21
nxxxf ,,, 21 1xf
dfxf 10
dfxf 01
Induction hypothesis: Lemma holds for Boolean expressions: E1 and E2 .
That is:
nnn xxxExxxExxxE ,,,,,,,,, 21221121
Induction step: show that it is true for E1’ ( E1 + E2 )
( E1 · E2 )
dn
dn
ExxxE
ExxxE
,2212
,1211
,,,
,,,
hypothesis induction ndnd xxxExxxE ,,,,,, 21,221,1
LawMorganDe ' nn xxxExxxE ,,,,,, 212211
nnn xxxExxxExxxE ,,,,,,,,, 21221121 If
then,
nd xxxE ,,, 21
xExExE
21
xExExE
21
hypothesis induction xExE dd
,2,1
LawMorganDe ' xExE 21
If
then,
xEd
xExE
1If
xExE 1
then,
xE
1
xE d
,1
xEd
hypothesis induction
Definition: A function f is called self-dual if f = fd
Lemma: For any function f and any two-valued variable A, the function g = Af + A’fd is a self-dual.
Proof: (holds for any Boolean algebra)
dfAAfdualgdual
dfAdualAfdual
dfdualAdualfdualAdual
fAfA d
ffAAfA dd
dd fAffAA
Dual definition
Distributivity
Commutativity
dd fAffAA
dd fffAfAAA
dd fffAfA 0
dd fffAfA
dd fffAAf
Notice that the above expression has the form:
ab + a’c +bc
where “a” =A, “b”=f, “c” = fd.
Distributivity
dd fffAfAAA Commutativity
A’ is the complement of A
Identity
Commutativity
We now prove a stronger claim:
caabbccaabBcba .,,
111 bccaabbccaab
aabccaab 11
abcbcacaab 11
cbaabccaab 11
11 cacbaababc
11 bcacab
11 caab
caab
Identity
a’ is the complement of a
Distributivity
Commutativity
Commutativity
Distributivity
Theorem: For any a B, a + 1 = 1
Identity
Easier proof (1) for switching algebra only: (using dual properties)
dd fffAAf
dfAAfdualgdual
Switching algebra
1 and 0 dff
0 and 1 dffOR 0dff
0 dfAAf
dfAAf Identity
A = 0dd ffffgdual 00)(
dd ffff 10
dd ffff 0
ffff dd 0
df0
df
dd fffg 00
0’ = 1
Identity
Commutativity
Absorption Law
Theorem: For any a B, a · 0 = 0
Identity
Easier proof (2) for switching algebra only: (case analysis)
dd fffAAf
dfAAfdualgdual
1,01,0: f
decreasing monotone xf
Example of a transfer function for an inverter
xf
xf
,0in decreasingstrictly xf
0.,0 xfx
0, interval in the concave xf
1,in increasingstrictly xf
0.1, xfx
,1 interval in theconvex is xf
1
1
outhighV ,
inhighV ,
outlowV ,
inlowV ,
slope = -1
slope = -1
x
xf
outlowinlowinhighouthigh VVVV ,,,,
true only if:
BUT, this is not always the case.
For example:
1
1 x
xf
outhighV ,
inhighV ,
outlowV ,
inlowV ,
slope = -1
slope = -1
outhighinhigh VV ,,
Moreover, in this example it can be proved that no threshold values exist, which are consistent with definition 3 from lecture notes.
Using the assumption:
00
2010
such that
:point a exists there
xxf
xxxx
slope < -1
f (x) = x
1
1 x
xf
1x 0x 2x
0,,,,
:start with
xVVVV outlowinlowinhighouthigh
0x 0x
0xf
0xf
y
x
xy
:set 0,, xVV inhighinhigh
0,, xVV inlowinlow
0,, xfVfV inlowouthigh
0,, xfVfV inhighoutlow
0xf
0x
0xf
0x
f (x) = x
1
1
slope < -1
x
xf
1x 0x 2x
0x 0x
0xf
0xf
y
x
xy