I was reading about horizontal and vertical parity check codes. One of the properties of these codes is that the final parity check (the lower right bit) is equal to modulo 2 sum of horizontal parity checks and also equal to modulo 2 of sum of vertical parity checks.
I did not understand, why this is true. I can see them in the examples but i really cant come up with any formal/intuitive proof about the same.
Any help/hints will be appreciated.
Thanks,
Chander
Each row and column is sum modulo 2. And result is sum of all numbers mod 2. It does not matter how you count.
Rule is:
((a mod c) + (b mod c)) mod c == (a+b) mod c
This is because every wrong bit propagates the parity either horizontally either vertically..
think about having your matrix of bits:
A B C D
E F G H
I J K L
M N O P
now some of these bits are wrongly transmitted, so you have a total of y errors that are layed around but you don't know where inside the matrix.
If you go by rows (so you calculate horizontal parity) you will be sure that the sum of every row parity modulo 2 will be 0 if you have an even number of errors in that row, 1 otherwise. You will be also sure of the fact that you are considering all of them since you do this work for every row.
Finally if you suppose to correct a bit from a row and alter another one in another one the final result won't change, since you basically remove 1 from a rows to add it elsewhere.
Then think about doing it by columns, you will end up with the same exact behaviour, the only difference is that errors can be distribuited in a different way but adding vertical parity together modulo 2 will take into account same considerations. Since the number of total errors is the same it will be an even number or an odd number either for rows and columns.
Related
I'm creating an encryptor/decryptor for ascii strings where I take the ascii value of a char, add 1 to it, then mod it by the highest ascii value so that I get a valid ascii char out.
The problem is the decryption.
Let's say that (a + b) % c = d
I know b, c, and d's values.
How do I get the a variables value out from that?
This is exactly the ROT1 substitution cipher. Subtract 1, and if less than lowest value (0 I assume, given how you're describing it), then add the highest value.
Using terms like "mod," while accurate, make this seem more complicated than it is. It's just addition on a ring. When you go past the last letter, you come back to the first letter and vice-versa. Once you put your head around how the math works, the equations should pop out. Basically, you just add or subtract as normal (add to encrypt, subtract to decrypt in this case), and at the end, mod "normalizes" you back onto the ring of legal values.
Use the inverse formula
a = (b - d) mod c
or in practice
a = (b - d + c) % c.
The term + c needs to be added as a safeguard because the % operator does not implement a true modulo in the negatives.
Let's assume that c is 2, d is 0 and b is 4.
Now we know that a must be 2... Or 4 actually.. or 6... Or any other even number.
You can't solve this problem, there are infinite solutions.
So in my text book there is this example of a recursive function using f#
let rec gcd = function
| (0,n) -> n
| (m,n) -> gcd(n % m,m);;
with this function my text book gives the example by executing:
gcd(36,116);;
and since the m = 36 and not 0 then it ofcourse goes for the second clause like this:
gcd(116 % 36,36)
gcd(8,36)
gcd(36 % 8,8)
gcd(4,8)
gcd(8 % 4,4)
gcd(0,4)
and now hits the first clause stating this entire thing is = 4.
What i don't get is this (%)percentage sign/operator or whatever it is called in this connection. for an instance i don't get how
116 % 36 = 8
I have turned this so many times in my head now and I can't figure how this can turn into 8?
I know this is probably a silly question for those of you who knows this but I would very much appreciate your help the same.
% is a questionable version of modulo, which is the remainder of an integer division.
In the positive, you can think of % as the remainder of the division. See for example Wikipedia on Euclidean Divison. Consider 9 % 4: 4 fits into 9 twice. But two times four is only eight. Thus, there is a remainder of one.
If there are negative operands, % effectively ignores the signs to calculate the remainder and then uses the sign of the dividend as the sign of the result. This corresponds to the remainder of an integer division that rounds to zero, i.e. -2 / 3 = 0.
This is a mathematically unusual definition of division and remainder that has some bad properties. Normally, when calculating modulo n, adding or subtracting n on the input has no effect. Not so for this operator: 2 % 3 is not equal to (2 - 3) % 3.
I usually have the following defined to get useful remainders when there are negative operands:
/// Euclidean remainder, the proper modulo operation
let inline (%!) a b = (a % b + b) % b
So far, this operator was valid for all cases I have encountered where a modulo was needed, while the raw % repeatedly wasn't. For example:
When filling rows and columns from a single index, you could calculate rowNumber = index / nCols and colNumber = index % nCols. But if index and colNumber can be negative, this mapping becomes invalid, while Euclidean division and remainder remain valid.
If you want to normalize an angle to (0, 2pi), angle %! (2. * System.Math.PI) does the job, while the "normal" % might give you a headache.
Because
116 / 36 = 3
116 - (3*36) = 8
Basically, the % operator, known as the modulo operator will divide a number by other and give the rest if it can't divide any longer. Usually, the first time you would use it to understand it would be if you want to see if a number is even or odd by doing something like this in f#
let firstUsageModulo = 55 %2 =0 // false because leaves 1 not 0
When it leaves 8 the first time means that it divided you 116 with 36 and the closest integer was 8 to give.
Just to help you in future with similar problems: in IDEs such as Xamarin Studio and Visual Studio, if you hover the mouse cursor over an operator such as % you should get a tooltip, thus:
Module operator tool tip
Even if you don't understand the tool tip directly, it'll give you something to google.
i want to know is it possible to validate that deviding two number has remaining zero in result or not?
for example dividing number 4 on number two has zero in remaining.
4/2=0 (this is true)
but 4/3=1 (this is not true)
is there any expression for validation such case?
Better Question :
Is There any validation expression to validate this sentence ?
Remainder is zero
thank you
You can use a Modulo operator. The modulo operation finds the remainder of division of one number by another
y mod x
5 mod 2 =1 (2x2=4, 5-4=1)
9 mod 3 = 0 (3*3=9)
You can think of it, how many times does x fit in y and then take the remainder.
In computing the modulo operator is integrated in most programming languages, along with division, substraction etc. Check modulo and then your language on google (probably its mod).
This is called the modulo function. It essentially gives the remainder of a division of two integer number. So you can test for the modulo funtion returning zero. For example, in Python you would write
if a % b == 0:
# a can be divided by b with zero remainder
Carry save arithmetic uses twice the number of bits, one word to hold the "virtual sum", one to hold the "virtual carry" to avoid propagating the carry which is the limiting factor in hardware speed.
I have a system that requires dividing these numbers by powers of two, but simply right shifting both numbers does not work in all cases eg. two 16 bit carry save numbers, which you add to produce 4000, C001 is the Virtual Sum, 7FFF is the virtual carry.
C001 + 7FFF = 4000 (discard overflow bits)
but after right shift
6000 + 3FFF = 9FFF (when it should be 2000)
In short: How do you divide a carry save number by a power of two? (While keeping it a carry save number)
First, right shift by 1 effectively does deleting by 2 with forgetting a remainder. But the remainder could be needed for having the exact result. For instance, change your initial example with adding C000 to 8000, or C002 to 7FFE. Both give the same sum but, sum of shifted values is A000 instead of your 9FFF, and this is definitely more correct. So, you can do such shifting only if sum of LSBs could be lost. In your case with 2 summands and 1 bit shift, this means no more than 1 summand could have 1 in its LSB.
Second, consider this is fixed and you've got A000. A simple ideal math says (a+b)/2 == a/2 + b/2. For your case, the carry bit you initially ignored weighed 0x10000, but after shifting by 1, it weighs 0x8000. That is exactly how A000 differs from your expected 2000. So, if you are sure in other aspects of your method, finish it with logical AND with ~0x8000 == 0x7FFF.
There is a technique to correct the representation such that it is shiftable. This originates from a paper "Carry-save architectures for high-speed digital signal processing" by Tobias Noll. You can compute new sign-bits of the carry and sum vectors as
c' = c_out
s' = s xor c xor c_out
where s and c are the original sign-bits and c_out is the discarded carry-bit from the carry-save addition.
I can have any number row which consists from 2 to 10 numbers. And from this row, I have to get geometrical progression.
For example:
Given number row: 125 5 625 I have to get answer 5. Row: 128 8 512 I have to get answer 4.
Can you give me a hand? I don't ask for a program, just a hint, I want to understand it by myself and write a code by myself, but damn, I have been thinking the whole day and couldn't figure this out.
Thank you.
DON'T WRITE THE WHOLE PROGRAM!
Guys, you don't get it, I can't just simple make a division. I actually have to get geometrical progression + show all numbers. In 128 8 512 row all numbers would be: 8 32 128 512
Seth's answer is the right one. I'm leaving this answer here to help elaborate on why the answer to 128 8 512 is 4 because people seem to be having trouble with that.
A geometric progression's elements can be written in the form c*b^n where b is the number you're looking for (b is also necessarily greater than 1), c is a constant and n is some arbritrary number.
So the best bet is to start with the smallest number, factorize it and look at all possible solutions to writing it in the c*b^n form, then using that b on the remaining numbers. Return the largest result that works.
So for your examples:
125 5 625
Start with 5. 5 is prime, so it can be written in only one way: 5 = 1*5^1. So your b is 5. You can stop now, assuming you know the row is in fact geometric. If you need to determine whether it's geometric then test that b on the remaining numbers.
128 8 512
8 can be written in more than one way: 8 = 1*8^1, 8 = 2*2^2, 8 = 2*4^1, 8 = 4*2^1. So you have three possible values for b, with a few different options for c. Try the biggest first. 8 doesn't work. Try 4. It works! 128 = 2*4^3 and 512 = 2*4^4. So b is 4 and c is 2.
3 15 375
This one is a bit mean because the first number is prime but isn't b, it's c. So you'll need to make sure that if your first b-candidate doesn't work on the remaining numbers you have to look at the next smallest number and decompose it. So here you'd decompose 15: 15 = 15*?^0 (degenerate case), 15 = 3*5^1, 15 = 5*3^1, 15 = 1*15^1. The answer is 5, and 3 = 3*5^0, so it works out.
Edit: I think this should be correct now.
This algorithm does not rely on factoring, only on the Euclidean Algorithm, and a close variant thereof. This makes it slightly more mathematically sophisticated then a solution that uses factoring, but it will be MUCH faster. If you understand the Euclidean Algorithm and logarithms, the math should not be a problem.
(1) Sort the set of numbers. You have numbers of the form ab^{n1} < .. < ab^{nk}.
Example: (3 * 2, 3*2^5, 3*2^7, 3*2^13)
(2) Form a new list whose nth element of the (n+1)st element of the sorted list divided by the (n)th. You now have b^{n2 - n1}, b^{n3 - n2}, ..., b^{nk - n(k-1)}.
(Continued) Example: (2^4, 2^2, 2^6)
Define d_i = n_(i+1) - n_i (do not program this -- you couldn't even if you wanted to, since the n_i are unknown -- this is just to explain how the program works).
(Continued) Example: d_1 = 4, d_2 = 2, d_3 = 6
Note that in our example problem, we're free to take either (a = 3, b = 2) or (a = 3/2, b = 4). The bottom line is any power of the "real" b that divides all entries in the list from step (2) is a correct answer. It follows that we can raise b to any power that divides all the d_i (in this case any power that divides 4, 2, and 6). The problem is we know neither b nor the d_i. But if we let m = gcd(d_1, ... d_(k-1)), then we CAN find b^m, which is sufficient.
NOTE: Given b^i and b^j, we can find b^gcd(i, j) using:
log(b^i) / log(b^j) = (i log b) / (j log b) = i/j
This permits us to use a modified version of the Euclidean Algorithm to find b^gcd(i, j). The "action" is all in the exponents: addition has been replaced by multiplication, multiplication with exponentiation, and (consequently) quotients with logarithms:
import math
def power_remainder(a, b):
q = int(math.log(a) / math.log(b))
return a / (b ** q)
def power_gcd(a, b):
while b != 1:
a, b = b, power_remainder(a, b)
return a
(3) Since all the elements of the original set differ by powers of r = b^gcd(d_1, ..., d_(k-1)), they are all of the form cr^n, as desired. However, c may not be an integer. Let me know if this is a problem.
The simplest approach would be to factorize the numbers and find the greatest number they have in common. But be careful, factorization has an exponential complexity so it might stop working if you get big numbers in the row.
What you want is to know the Greatest Common Divisor of all numbers in a row.
One method is to check if they all can be divided by the smaller number in the row.
If not, try half the smaller number in the row.
Then keep going down until you find a number that divides them all or your divisor equals 1.
Seth Answer is not correct, applyin that solution does not solves 128 8 2048 row for example (2*4^x), you get:
8 128 2048 =>
16 16 =>
GCD = 16
It is true that the solution is a factor of this result but you will need to factor it and check one by one what is the correct answer, in this case you will need to check the solutions factors in reverse order 16, 8, 4, 2 until you see 4 matches all the conditions.