Boolean Logic and Expression - boolean-logic

Simplify the expression below using boolean algebra theorem.
A XOR B XOR A XOR ~ B
outline each step and indicate which law you're using in each step please.

Too simple, isn't it?
A⊕B⊕A⊕~B => A⊕A⊕B⊕~B => (A⊕A)⊕(B⊕~B)
A⊕A=0 (1⊕1=0, 0⊕0=0)
B⊕~B=1 (1⊕0=1, 0⊕1=1)
1⊕0=1
It refers to basics of this operation.

Maybe you were hoping for something like this...
A XOR B XOR A XOR ~ B
(A XOR (B XOR (A XOR (~B)))) Parenthesized
(A XOR ((A XOR (~B)) XOR B)) Commutative
((A XOR (A XOR (~B))) XOR B) Associative
(((A XOR A) XOR (~B)) XOR B) Associative
((0 XOR (~B)) XOR B) A XOR A = 0 for all A; not sure of name
(~B XOR B) 0 XOR A = A for all A; not sure of name
1 A XOR ~A = 1 for all A; not sure of name
Not sure what a few of those properties are named... the definition of XOR? These may be properties that are proven from simpler notions. In any event, they are neither commutativity nor associativity. Anyway, hope this helped.

Related

Why cant i have a "equal" rational function

i am very new to the haskell and have a question about Eq.
data Rat = Rat Integer Integer
normaliseRat :: Rat -> Rat
normaliseRat (Rat x y)
|x < 0 && y < 0 = Rat (-x) (-y)
|otherwise = Rat (x `div`(gcd x y)) (y `div` (gcd x y))
So i have a func normaliseRat. And what i need is an instance of Eq and Ord. Of course, Rat 2 4 == Rat 1 2 should be valid.
Thanks for help
Haskell doesn't support function overloading. But (==) isn't a function; it's declared as a typeclass method, so any type-specific implementations of the method must be defined within an instance declaration, like so:
instance Eq Rat where
(Rat x y) == (Rat n m) = x * m == y * n
(x/y == n/m is equivalent, after cross multiplying, to x * m == y * n; multiplication is more efficient and has none of accuracy issues that division would introduce.)
The same applies to Ord, except you have your choice of implementing (<=) or compare. (Given either of those, default definitions for the other comparison methods will work.)
instance Ord Rat where
-- I leave fixing this to accommodate negative numbers
-- correctly as an exercise.
(Rat x y) <= (Rat n m) = (x * m) <= (y * n)
As a typeclass method, (==) is really an entire family of functions, indexed by the type it's being used with. The purpose of the instance declaration is not to redefine the method, but to add a new function to that family.
If you enable the TypeApplications extension, you can view (==) as a mapping from a type to a function.
> :t (==)
(==) :: Eq a => a -> a -> Bool
> :t (==) #Int
(==) #Int :: Int -> Int -> Bool
Without a type application, Haskell's type checker automatically figures out which function to use:
> (==) 'c' 'd'
False
> (==) 3 5
False
but you can be explicit:
> (==) #Char 'c 'd'
False
> (==) #Char 3 5
<interactive>:9:12: error:
• No instance for (Num Char) arising from the literal ‘3’
• In the second argument of ‘(==)’, namely ‘3’
In the expression: (==) #Char 3 5
In an equation for ‘it’: it = (==) #Char 3 5

Finding inverse functions [duplicate]

In pure functional languages like Haskell, is there an algorithm to get the inverse of a function, (edit) when it is bijective? And is there a specific way to program your function so it is?
In some cases, yes! There's a beautiful paper called Bidirectionalization for Free! which discusses a few cases -- when your function is sufficiently polymorphic -- where it is possible, completely automatically to derive an inverse function. (It also discusses what makes the problem hard when the functions are not polymorphic.)
What you get out in the case your function is invertible is the inverse (with a spurious input); in other cases, you get a function which tries to "merge" an old input value and a new output value.
No, it's not possible in general.
Proof: consider bijective functions of type
type F = [Bit] -> [Bit]
with
data Bit = B0 | B1
Assume we have an inverter inv :: F -> F such that inv f . f ≡ id. Say we have tested it for the function f = id, by confirming that
inv f (repeat B0) -> (B0 : ls)
Since this first B0 in the output must have come after some finite time, we have an upper bound n on both the depth to which inv had actually evaluated our test input to obtain this result, as well as the number of times it can have called f. Define now a family of functions
g j (B1 : B0 : ... (n+j times) ... B0 : ls)
= B0 : ... (n+j times) ... B0 : B1 : ls
g j (B0 : ... (n+j times) ... B0 : B1 : ls)
= B1 : B0 : ... (n+j times) ... B0 : ls
g j l = l
Clearly, for all 0<j≤n, g j is a bijection, in fact self-inverse. So we should be able to confirm
inv (g j) (replicate (n+j) B0 ++ B1 : repeat B0) -> (B1 : ls)
but to fulfill this, inv (g j) would have needed to either
evaluate g j (B1 : repeat B0) to a depth of n+j > n
evaluate head $ g j l for at least n different lists matching replicate (n+j) B0 ++ B1 : ls
Up to that point, at least one of the g j is indistinguishable from f, and since inv f hadn't done either of these evaluations, inv could not possibly have told it apart – short of doing some runtime-measurements on its own, which is only possible in the IO Monad.
                                                                                                                                   ⬜
You can look it up on wikipedia, it's called Reversible Computing.
In general you can't do it though and none of the functional languages have that option. For example:
f :: a -> Int
f _ = 1
This function does not have an inverse.
Not in most functional languages, but in logic programming or relational programming, most functions you define are in fact not functions but "relations", and these can be used in both directions. See for example prolog or kanren.
Tasks like this are almost always undecidable. You can have a solution for some specific functions, but not in general.
Here, you cannot even recognize which functions have an inverse. Quoting Barendregt, H. P. The Lambda Calculus: Its Syntax and Semantics. North Holland, Amsterdam (1984):
A set of lambda-terms is nontrivial if it is neither the empty nor the full set. If A and B are two nontrivial, disjoint sets of lambda-terms closed under (beta) equality, then A and B are recursively inseparable.
Let's take A to be the set of lambda terms that represent invertible functions and B the rest. Both are non-empty and closed under beta equality. So it's not possible to decide whether a function is invertible or not.
(This applies to the untyped lambda calculus. TBH I don't know if the argument can be directly adapted to a typed lambda calculus when we know the type of a function that we want to invert. But I'm pretty sure it will be similar.)
If you can enumerate the domain of the function and can compare elements of the range for equality, you can - in a rather straightforward way. By enumerate I mean having a list of all the elements available. I'll stick to Haskell, since I don't know Ocaml (or even how to capitalise it properly ;-)
What you want to do is run through the elements of the domain and see if they're equal to the element of the range you're trying to invert, and take the first one that works:
inv :: Eq b => [a] -> (a -> b) -> (b -> a)
inv domain f b = head [ a | a <- domain, f a == b ]
Since you've stated that f is a bijection, there's bound to be one and only one such element. The trick, of course, is to ensure that your enumeration of the domain actually reaches all the elements in a finite time. If you're trying to invert a bijection from Integer to Integer, using [0,1 ..] ++ [-1,-2 ..] won't work as you'll never get to the negative numbers. Concretely, inv ([0,1 ..] ++ [-1,-2 ..]) (+1) (-3) will never yield a value.
However, 0 : concatMap (\x -> [x,-x]) [1..] will work, as this runs through the integers in the following order [0,1,-1,2,-2,3,-3, and so on]. Indeed inv (0 : concatMap (\x -> [x,-x]) [1..]) (+1) (-3) promptly returns -4!
The Control.Monad.Omega package can help you run through lists of tuples etcetera in a good way; I'm sure there's more packages like that - but I don't know them.
Of course, this approach is rather low-brow and brute-force, not to mention ugly and inefficient! So I'll end with a few remarks on the last part of your question, on how to 'write' bijections. The type system of Haskell isn't up to proving that a function is a bijection - you really want something like Agda for that - but it is willing to trust you.
(Warning: untested code follows)
So can you define a datatype of Bijection s between types a and b:
data Bi a b = Bi {
apply :: a -> b,
invert :: b -> a
}
along with as many constants (where you can say 'I know they're bijections!') as you like, such as:
notBi :: Bi Bool Bool
notBi = Bi not not
add1Bi :: Bi Integer Integer
add1Bi = Bi (+1) (subtract 1)
and a couple of smart combinators, such as:
idBi :: Bi a a
idBi = Bi id id
invertBi :: Bi a b -> Bi b a
invertBi (Bi a i) = (Bi i a)
composeBi :: Bi a b -> Bi b c -> Bi a c
composeBi (Bi a1 i1) (Bi a2 i2) = Bi (a2 . a1) (i1 . i2)
mapBi :: Bi a b -> Bi [a] [b]
mapBi (Bi a i) = Bi (map a) (map i)
bruteForceBi :: Eq b => [a] -> (a -> b) -> Bi a b
bruteForceBi domain f = Bi f (inv domain f)
I think you could then do invert (mapBi add1Bi) [1,5,6] and get [0,4,5]. If you pick your combinators in a smart way, I think the number of times you'll have to write a Bi constant by hand could be quite limited.
After all, if you know a function is a bijection, you'll hopefully have a proof-sketch of that fact in your head, which the Curry-Howard isomorphism should be able to turn into a program :-)
I've recently been dealing with issues like this, and no, I'd say that (a) it's not difficult in many case, but (b) it's not efficient at all.
Basically, suppose you have f :: a -> b, and that f is indeed a bjiection. You can compute the inverse f' :: b -> a in a really dumb way:
import Data.List
-- | Class for types whose values are recursively enumerable.
class Enumerable a where
-- | Produce the list of all values of type #a#.
enumerate :: [a]
-- | Note, this is only guaranteed to terminate if #f# is a bijection!
invert :: (Enumerable a, Eq b) => (a -> b) -> b -> Maybe a
invert f b = find (\a -> f a == b) enumerate
If f is a bijection and enumerate truly produces all values of a, then you will eventually hit an a such that f a == b.
Types that have a Bounded and an Enum instance can be trivially made RecursivelyEnumerable. Pairs of Enumerable types can also be made Enumerable:
instance (Enumerable a, Enumerable b) => Enumerable (a, b) where
enumerate = crossWith (,) enumerate enumerate
crossWith :: (a -> b -> c) -> [a] -> [b] -> [c]
crossWith f _ [] = []
crossWith f [] _ = []
crossWith f (x0:xs) (y0:ys) =
f x0 y0 : interleave (map (f x0) ys)
(interleave (map (flip f y0) xs)
(crossWith f xs ys))
interleave :: [a] -> [a] -> [a]
interleave xs [] = xs
interleave [] ys = []
interleave (x:xs) ys = x : interleave ys xs
Same goes for disjunctions of Enumerable types:
instance (Enumerable a, Enumerable b) => Enumerable (Either a b) where
enumerate = enumerateEither enumerate enumerate
enumerateEither :: [a] -> [b] -> [Either a b]
enumerateEither [] ys = map Right ys
enumerateEither xs [] = map Left xs
enumerateEither (x:xs) (y:ys) = Left x : Right y : enumerateEither xs ys
The fact that we can do this both for (,) and Either probably means that we can do it for any algebraic data type.
Not every function has an inverse. If you limit the discussion to one-to-one functions, the ability to invert an arbitrary function grants the ability to crack any cryptosystem. We kind of have to hope this isn't feasible, even in theory!
In some cases, it is possible to find the inverse of a bijective function by converting it into a symbolic representation. Based on this example, I wrote this Haskell program to find inverses of some simple polynomial functions:
bijective_function x = x*2+1
main = do
print $ bijective_function 3
print $ inverse_function bijective_function (bijective_function 3)
data Expr = X | Const Double |
Plus Expr Expr | Subtract Expr Expr | Mult Expr Expr | Div Expr Expr |
Negate Expr | Inverse Expr |
Exp Expr | Log Expr | Sin Expr | Atanh Expr | Sinh Expr | Acosh Expr | Cosh Expr | Tan Expr | Cos Expr |Asinh Expr|Atan Expr|Acos Expr|Asin Expr|Abs Expr|Signum Expr|Integer
deriving (Show, Eq)
instance Num Expr where
(+) = Plus
(-) = Subtract
(*) = Mult
abs = Abs
signum = Signum
negate = Negate
fromInteger a = Const $ fromIntegral a
instance Fractional Expr where
recip = Inverse
fromRational a = Const $ realToFrac a
(/) = Div
instance Floating Expr where
pi = Const pi
exp = Exp
log = Log
sin = Sin
atanh = Atanh
sinh = Sinh
cosh = Cosh
acosh = Acosh
cos = Cos
tan = Tan
asin = Asin
acos = Acos
atan = Atan
asinh = Asinh
fromFunction f = f X
toFunction :: Expr -> (Double -> Double)
toFunction X = \x -> x
toFunction (Negate a) = \a -> (negate a)
toFunction (Const a) = const a
toFunction (Plus a b) = \x -> (toFunction a x) + (toFunction b x)
toFunction (Subtract a b) = \x -> (toFunction a x) - (toFunction b x)
toFunction (Mult a b) = \x -> (toFunction a x) * (toFunction b x)
toFunction (Div a b) = \x -> (toFunction a x) / (toFunction b x)
with_function func x = toFunction $ func $ fromFunction x
simplify X = X
simplify (Div (Const a) (Const b)) = Const (a/b)
simplify (Mult (Const a) (Const b)) | a == 0 || b == 0 = 0 | otherwise = Const (a*b)
simplify (Negate (Negate a)) = simplify a
simplify (Subtract a b) = simplify ( Plus (simplify a) (Negate (simplify b)) )
simplify (Div a b) | a == b = Const 1.0 | otherwise = simplify (Div (simplify a) (simplify b))
simplify (Mult a b) = simplify (Mult (simplify a) (simplify b))
simplify (Const a) = Const a
simplify (Plus (Const a) (Const b)) = Const (a+b)
simplify (Plus a (Const b)) = simplify (Plus (Const b) (simplify a))
simplify (Plus (Mult (Const a) X) (Mult (Const b) X)) = (simplify (Mult (Const (a+b)) X))
simplify (Plus (Const a) b) = simplify (Plus (simplify b) (Const a))
simplify (Plus X a) = simplify (Plus (Mult 1 X) (simplify a))
simplify (Plus a X) = simplify (Plus (Mult 1 X) (simplify a))
simplify (Plus a b) = (simplify (Plus (simplify a) (simplify b)))
simplify a = a
inverse X = X
inverse (Const a) = simplify (Const a)
inverse (Mult (Const a) (Const b)) = Const (a * b)
inverse (Mult (Const a) X) = (Div X (Const a))
inverse (Plus X (Const a)) = (Subtract X (Const a))
inverse (Negate x) = Negate (inverse x)
inverse a = inverse (simplify a)
inverse_function x = with_function inverse x
This example only works with arithmetic expressions, but it could probably be generalized to work with lists as well. There are also several implementations of computer algebra systems in Haskell that may be used to find the inverse of a bijective function.
No, not all functions even have inverses. For instance, what would the inverse of this function be?
f x = 1

Build x XOR (y XOR z) with NAND port

I need to make x xor(y xor z) with only NAND ports.
Notation: NOT(y) = ~y.
My first steps were to identify the output of that stuff, so:
x xor(y xor z) = x xor (y~z + ~yz) = ~x(y~z + ~yz) + x~(y~z + ~yz) = ~xy~z + ~x~yz + x~y~z + xyz
So the final output of my NAND construction should be: ~xy~z + ~x~yz + x~y~z + xyz
I tried to attack this by first making y XOR z:
y XOR z = y~z + ~yz = NAND[NAND(y,NAND(z,z)),NAND(z,NAND(y,y))]
Since
NAND(y,NAND(z,z)) = NOT(y * NOT(z*z)) = NOT(y) + z which I'll call g1 and
NAND(z,NAND(y,y)) = NOT(z * NOT(y*y)) = NOT(z) + y as g2
then the outside NAND[g1,g2] = z~y + y~z.
So now I have a XOR with just NANDs and doing the x xor (y xor z) should be just matter of treating (y xor z) as a single variable which gives me:
x xor (y xor z) = NAND[NAND(x,NAND(NAND[NAND(y,NAND(z,z)),NAND(z,NAND(y,y))],NAND[NAND(y,NAND(z,z)),NAND(z,NAND(y,y))])),NAND(NAND[NAND(y,NAND(z,z)),NAND(z,NAND(y,y))],NAND(x,x))]
Am I correct? I feel like the xor could be made in a more efficient way than using 5 NANDs ports.
Thanks guys.
Your final expression is correct.
The 20 NAND gates can be reduced to eight:
This circuit makes use of XOR(x,y,z) = XOR(XOR(x,y),z). It is a combination of two two-input XOR gates, each of them composed of four NAND gates.

How do we solve p xor 1 xor q? How to verify if the result is correct?

What is the equation we get when we do (p xor q xor 1)
I know that (p xor 1) is p'
Is (p xor q xor 1) = (p xor q') or (p' xor q')?
Please help me. How do we verify these things?
Since all the operators are the same, they will have the same priority so (p xor q xor 1) will be equivalent to this:
(p xor q)xor 1
which is equivalent to:
(p xor q)'
How to verify this.
Let's build a truth table and see how the results compares for another equation.
And p xor q xor 1 can be read as (p xor q) xor 1.
Of course we assume that 1 stands for true and 0 for false.
p q p xor q xor 1
0 0 1
0 1 0
1 0 0
1 1 1
This will give the same results as p xnor q
p q p xnor q
0 0 1
0 1 0
1 0 0
1 1 1
not(p xor q) , p xor not q , not(p) xor not(q) will give the same results.

How to writer the condition A or B is zero , but not both is zero in MYSQL?

What is the correct syntax for the following SQL statement ?
SELECT * FROM TABLE WHERE (A = 0 AND B != 0) OR (A!=0 AND B=0)
Thanks
Updated: How about negative case? I would like to check if A or B is non-zero , but not both is non-zero, Thanks
SELECT OperateProductId FROM DPS_UserLoginStatus Where OperateProductId <> 0 XOR OperateIssueId <> 0
You're looking for the XOR logical operator:
SELECT * FROM TABLE WHERE A = 0 XOR B = 0
In terms of other operators, a XOR b (commonly a ^ b when used bitwise rather than logical), is equivalent to (a and !b) or (b and !a). It's also equivalent to: (a or b) and (!a or !b). In English, it's exactly what you're looking for: a xor b is true if and only if either a or b is true but both are not true.