Design a Turing machine that takes input two non-negative numbers and performs the mod operation on them, for example, mod(3,7)=3 and mod(7,3)=1. Clearly, specify any assumptions and formats about the input and output of the TM.
Input is two positive integers X and Y in unary separated by a separator symbol. Output is a single number Z in unary. TM is single sided single tape deterministic.
First, move right to find the separator. Then, bounce back and forth between the end of X and the beginning of Y, marking pairs of symbols. If you run out of X before running out of Y, then X < Y and X mod Y = X; erase the separator and everything after it, then change all tape symbols to your unary digit and halt-accept. If you run out of Y before X, then change marked symbols in X to erased/separator, restore marked symbols of Y to the unary digit, and repeat (X >= Y, so X mod Y = (X - Y) mod Y).
Here's how your 2 mod 3 gets processed:
#110111#
#1a0b11#
#aa0bb1#
#aa#####
#11#####
Here's how 3 mod 2 gets processed:
#111011#
#11a0b1#
#1aa0bb#
#100011#
#a000b1#
#a######
#1######
some basic information is given below
![enter image description here
complete figure is given below. here # is empty or null.Idea is same as given above.
Here's how your 2 mod 3 gets processed:
#110111#
#1a0b11#
#aa0bb1#
#aa#####
#11#####
Here's how 3 mod 2 gets processed:
#111011#
#11a0b1#
#1aa0bb#
#100011#
#a000b1#
#a######
#1######
Related
Is there a way to vectorize this FOR loop I know about gallery ("circul",y) thanks to user carandraug
but this will only shift the cell over to the next adjacent cell I also tried toeplitz but that didn't work).
I'm trying to make the shift adjustable which is done in the example code with circshift and the variable shift_over.
The variable y_new is the output I'm trying to get but without having to use a FOR loop in the example (can this FOR loop be vectorized).
Please note: The numbers that are used in this example are just an example the real array will be voice/audio 30-60 second signals (so the y_new array could be large) and won't be sequential numbers like 1,2,3,4,5.
tic
y=[1:5];
[rw col]= size(y); %get size to create zero'd array
y_new= zeros(max(rw,col),max(rw,col)); %zero fill new array for speed
shift_over=-2; %cell amount to shift over
for aa=1:length(y)
if aa==1
y_new(aa,:)=y; %starts with original array
else
y_new(aa,:)=circshift(y,[1,(aa-1)*shift_over]); %
endif
end
y_new
fprintf('\nfinally Done-elapsed time -%4.4fsec- or -%4.4fmins- or -%4.4fhours-\n',toc,toc/60,toc/3600);
y_new =
1 2 3 4 5
3 4 5 1 2
5 1 2 3 4
2 3 4 5 1
4 5 1 2 3
Ps: I'm using Octave 4.2.2 Ubuntu 18.04 64bit.
I'm pretty sure this is a classic XY problem where you want to calculate something and you think it's a good idea to build a redundant n x n matrix where n is the length of your audio file in samples. Perhaps you want to play with autocorrelation but the key point here is that I doubt that building the requested matrix is a good idea but here you go:
Your code:
y = rand (1, 3e3);
shift_over = -2;
clear -x y shift_over
tic
[rw col]= size(y); %get size to create zero'd array
y_new= zeros(max(rw,col),max(rw,col)); %zero fill new array for speed
for aa=1:length(y)
if aa==1
y_new(aa,:)=y; %starts with original array
else
y_new(aa,:)=circshift(y,[1,(aa-1)*shift_over]); %
endif
end
toc
my code:
clear -x y shift_over
tic
n = numel (y);
y2 = y (mod ((0:n-1) - shift_over * (0:n-1).', n) + 1);
toc
gives on my system:
Elapsed time is 1.00379 seconds.
Elapsed time is 0.155854 seconds.
I am starting to use Octave and I am trying to understand how is the underlying calculation done for dividing a Scalar by vector ?
I am able to understand how ./ is operating to give us the results - dividing 1 by every element of the matrix column. However, I am not able to get my head around how we get the values in the second case ? 1 / (1 + a)
Example :
g = 1 ./ (1 + a)
g =
0.50000
0.25000
0.20000
>> g = 1 / (1 + a)
g =
0.044444 0.088889 0.111111
When you divide 1 by a vector, it gives you a vector that yields 1 when multiplied on the left by the first vector. In this sense, it is a sort of 'inverse' of the vector, although it will only be a one way inverse. In your example:
>> (1/(1+a))*(1+a)
ans = 1
>> (1+a)*(1/(1+a))
ans =
0.088889 0.177778 0.222222
0.177778 0.355556 0.444444
0.222222 0.444444 0.555556
You could say 1/(1+a) is the left inverse of 1+a. This would also explain why the dimensions of the vector are transposed. Another way to put it: given a vector v, 1/v is the solution (w) of the vector equation w*v=1.
I have been given this question to work on a solution. I'm struggling to get my head around the recursion. Some break down of the question would be very helpful.
Given that Pi can be estimated using the function 4 * (1 – 1/3 + 1/5 – 1/7 + …) with more terms giving greater accuracy, write a function that calculates Pi to an accuracy of 5 decimal places.
I have got some example code however I really don't understand where/why the variables are entered like this. Possible breakdown of this code and why it is not accurate would be appreciated.
-module (pi).
-export ([pi/0]).
pi() -> 4 * pi(0,1,1).
pi(T,M,D) ->
A = 1 / D,
if
A > 0.00001 -> pi(T+(M*A), M*-1, D+2);
true -> T
end.
The formula comes from the evaluation of tg(pi/4) which is equal to 1. The inverse:
pi/4 = arctg(1)
so
pi = 4* arctg(1).
using the technique of the Taylor series:
arctg (x) = x - x^3/3 + ... + (-1)^n x^(2n+1)/(2n+1) + o(x^(2n+1))
so when x = 1 you get your formula:
pi = 4 * (1 – 1/3 + 1/5 – 1/7 + …)
the problem is to find an approximation of pi with an accuracy of 0.00001 (5 decimal). Lookinq at the formula, you can notice that
at each step (1/3, 1/5,...) the new term to add:
is smaller than the previous one,
has the opposite sign.
This means that each term is an upper estimation of the error (the term o(x^(2n+1))) between the real value of pi and the evaluation up to this term.
So it can be use to stop the recursion at a level where it is guaranty that the approximation is better than this term. To be correct, the program
you propose multiply the final result of the recursion by 4, so the error is no more guaranteed to be smaller than term.
looking at the code:
pi() -> 4 * pi(0,1,1).
% T = 0 is the initial estimation
% M = 1 is the sign
% D = 1 initial value of the term's index in the Taylor serie
pi(T,M,D) ->
A = 1 / D,
% evaluate the term value
if
A > 0.00001 -> pi(T+(M*A), M*-1, D+2);
% if the precision is not reach call the pi function with,
% new serie's evaluation (the previous one + sign * term): T+(M*A)
% new inverted sign: M*-1
% new index: D+2
true -> T
% if the precision is reached, give the result T
end.
To be sure that you have reached the right accuracy, I propose to replace A > 0.00001 by A > 0.0000025 (= 0.00001/4)
I can't find any error in this code, but I can't test it right now, anyway:
T is probably "total", M is "multiplicator", and D is "divisor".
By every step you:
check (the 'if' is in some way similar to a switch/case in c/c++/java) if the next term (A = 1/D) is bigger than 0.00001. If not, you can stop the recursion, you've got the 5 decimal places you were looking for. So "if true (default case) -> return T"
if it's bigger, you multiply A by M, add to the total, then multiply M by -1, add 2 to D, and repeat (so you get the next term, add again, and so on).
pi(T,M,D) ->
A = 1 / D,
if
A > 0.00001 -> pi(T+(M*A), M*-1, D+2);
true -> T
end.
I don't know Erlang myself but from the looks of it you are checking if 1/D is < 0.00001 when in reality you should be checking 4 * 1/D because that 4 is going to be multiplied through. For example in your case if 1/D was 0.000003 you would stop four function, but your total would actually have changed by 0.000012. Hope this helps.
I have short, variable length decimal numbers, like: #41551, that are manually transcribed by humans. Mistyping one will cause undesirable results, so my first thought is to use the Luhn algorithm to add a checksum -- #41551-3. However, that will only detect an error, not correct it. It seems adding another check digit should be able to detect and correct a single-digit error, so given #41515-3? (a transposition error) I'd be able to recover the correct #41551.
Something like a Hamming code seems like the right place to look, but I haven't been able to figure out how to apply them to decimal, instead of binary, data. Is there an algorithm intended for this use, or can Hamming/Reed-Solomon etc be adapted to this situation?
Yes, you can use Hamming codes in addition with check equations for correction. Use summation of data modulo 10 for finding check digits. Place check digits in 1,2,4,8, ... positions.
I can only provide an algorithm with FIVE extra digits.
Note: 5 original digits is really a worst case.
With FIVE extra digits you can do ECC for up to 11 original digits.
This like classical ECC calculations but in decimal:
Original (decimal) 5-digit number: o0,o1,o2,o3,o4
Distribute digits to positions 0..9 in the following manner:
0 1 2 3 4 5 6 7 8 9
o0 o1 o2 o3 o4
c4 c0 c1 c2 c3 <- will be calculated check digits
Calculate digits at positions 1,2,4,8 like this:
c0, pos 1: (10 - (Sum positions 3,5,7,9)%10)%10
c1, pos 2: (10 - (Sum positions 3,6,7)%10)%10
c2, pos 4: (10 - (Sum positions 5,6,7)%10)%10
c3, pos 8: (10 - (Sum positions 9)%10)%10
AFTER this calculation, calculate digit at position:
c4, pos 0: (10 - (Sum positions 1..9)%10)%10
You might then reshuffle like this:
o0o1o2o3o4-c0c1c2c3c4
To check write all digits in the following order:
0 1 2 3 4 5 6 7 8 9
c4 c0 c1 o0 c2 o1 o2 o3 c3 o4
Then calculate:
c0' = (Sum positions 1,3,5,7,9)%10
c1' = (Sum positions 2,3,6,7)%10
c2' = (Sum positions 4,5,6,7)%10
c3' = (Sum positions 8,9)%10
c4' = (Sum all positions)%10
If c0',c1',c2',c3',c4' are all zero then there is no error.
If there are some c[0..3]' which are non-zero and ALL of the non-zero
c[0..3]' have the value c4', then there is an error in one digit.
You can calculate the position of the erroneous digit and correct.
(Exercise left to the reader).
If c[0..3]' are all zero and only c4' is unequal zero, then you have a one digit error in c4.
If a c[0..3]' is unequal zero and has a different value than c4' then you have (at least) an uncorrectable double error in two digits.
I tried to use Reed-Solomon, generating a 3-digit code that can correct up to 1 digit: https://epxx.co/artigos/edc2_en.html
I need to write a function that takes 4 bytes as input, performs a reversible linear transformation on this, and returns it as 4 bytes.
But wait, there is more: it also has to be distributive, so changing one byte on the input should affect all 4 output bytes.
The issues:
if I use multiplication it won't be reversible after it is modded 255 via the storage as a byte (and its needs to stay as a byte)
if I use addition it can't be reversible and distributive
One solution:
I could create an array of bytes 256^4 long and fill it in, in a one to one mapping, this would work, but there are issues: this means I have to search a graph of size 256^8 due to having to search for free numbers for every value (should note distributivity should be sudo random based on a 64*64 array of byte). This solution also has the MINOR (lol) issue of needing 8GB of RAM, making this solution nonsense.
The domain of the input is the same as the domain of the output, every input has a unique output, in other words: a one to one mapping. As I noted on "one solution" this is very possible and I have used that method when a smaller domain (just 256) was in question. The fact is, as numbers get big that method becomes extraordinarily inefficient, the delta flaw was O(n^5) and omega was O(n^8) with similar crappiness in memory usage.
I was wondering if there was a clever way to do it. In a nutshell, it's a one to one mapping of domain (4 bytes or 256^4). Oh, and such simple things as N+1 can't be used, it has to be keyed off a 64*64 array of byte values that are sudo random but recreatable for reverse transformations.
Balanced Block Mixers are exactly what you're looking for.
Who knew?
Edit! It is not possible, if you indeed want a linear transformation. Here's the mathy solution:
You've got four bytes, a_1, a_2, a_3, a_4, which we'll think of as a vector a with 4 components, each of which is a number mod 256. A linear transformation is just a 4x4 matrix M whose elements are also numbers mod 256. You have two conditions:
From Ma, we can deduce a (this means that M is an invertible matrix).
If a and a' differ in a single coordinate, then Ma and Ma' must differ in every coordinate.
Condition (2) is a little trickier, but here's what it means. Since M is a linear transformation, we know that
M(a - a) = Ma - Ma'
On the left, since a and a' differ in a single coordinate, a - a has exactly one nonzero coordinate. On the right, since Ma and Ma' must differ in every coordinate, Ma - Ma' must have every coordinate nonzero.
So the matrix M must take a vector with a single nonzero coordinate to one with all nonzero coordinates. So we just need every entry of M to be a non-zero-divisor mod 256, i.e., to be odd.
Going back to condition (1), what does it mean for M to be invertible? Since we're considering it mod 256, we just need its determinant to be invertible mod 256; that is, its determinant must be odd.
So you need a 4x4 matrix with odd entries mod 256 whose determinant is odd. But this is impossible! Why? The determinant is computed by summing various products of entries. For a 4x4 matrix, there are 4! = 24 different summands, and each one, being a product of odd entries, is odd. But the sum of 24 odd numbers is even, so the determinant of such a matrix must be even!
Here are your requirements as I understand them:
Let B be the space of bytes. You want a one-to-one (and thus onto) function f: B^4 -> B^4.
If you change any single input byte, then all output bytes change.
Here's the simplest solution I have thusfar. I have avoided posting for a while because I kept trying to come up with a better solution, but I haven't thought of anything.
Okay, first of all, we need a function g: B -> B which takes a single byte and returns a single byte. This function must have two properties: g(x) is reversible, and x^g(x) is reversible. [Note: ^ is the XOR operator.] Any such g will do, but I will define a specific one later.
Given such a g, we define f by f(a,b,c,d) = (a^b^c^d, g(a)^b^c^d, a^g(b)^c^d, a^b^g(c)^d). Let's check your requirements:
Reversible: yes. If we XOR the first two output bytes, we get a^g(a), but by the second property of g, we can recover a. Similarly for the b and c. We can recover d after getting a,b, and c by XORing the first byte with (a^b^c).
Distributive: yes. Suppose b,c, and d are fixed. Then the function takes the form f(a,b,c,d) = (a^const, g(a)^const, a^const, a^const). If a changes, then so will a^const; similarly, if a changes, so will g(a), and thus so will g(a)^const. (The fact that g(a) changes if a does is by the first property of g; if it didn't then g(x) wouldn't be reversible.) The same holds for b and c. For d, it's even easier because then f(a,b,c,d) = (d^const, d^const, d^const, d^const) so if d changes, every byte changes.
Finally, we construct such a function g. Let T be the space of two-bit values, and h : T -> T the function such that h(0) = 0, h(1) = 2, h(2) = 3, and h(3) = 1. This function has the two desired properties of g, namely h(x) is reversible and so is x^h(x). (For the latter, check that 0^h(0) = 0, 1^h(1) = 3, 2^h(2) = 1, and 3^h(3) = 2.) So, finally, to compute g(x), split x into four groups of two bits, and take h of each quarter separately. Because h satisfies the two desired properties, and there's no interaction between the quarters, so does g.
I'm not sure I understand your question, but I think I get what you're trying to do.
Bitwise Exclusive Or is your friend.
If R = A XOR B, R XOR A gives B and R XOR B gives A back. So it's a reversible transformation, assuming you know the result and one of the inputs.
Assuming I understood what you're trying to do, I think any block cipher will do the job.
A block cipher takes a block of bits (say 128) and maps them reversibly to a different block with the same size.
Moreover, if you're using OFB mode you can use a block cipher to generate an infinite stream of pseudo-random bits. XORing these bits with your stream of bits will give you a transformation for any length of data.
I'm going to throw out an idea that may or may not work.
Use a set of linear functions mod 256, with odd prime coefficients.
For example:
b0 = 3 * a0 + 5 * a1 + 7 * a2 + 11 * a3;
b1 = 13 * a0 + 17 * a1 + 19 * a2 + 23 * a3;
If I remember the Chinese Remainder Theorem correctly, and I haven't looked at it in years, the ax are recoverable from the bx. There may even be a quick way to do it.
This is, I believe, a reversible transformation. It's linear, in that af(x) mod 256 = f(ax) and f(x) + f(y) mod 256 = f(x + y). Clearly, changing one input byte will change all the output bytes.
So, go look up the Chinese Remainder Theorem and see if this works.
What you mean by "linear" transformation?
O(n), or a function f with f(c * (a+b)) = c * f(a) + c * f(b)?
An easy approach would be a rotating bitshift (not sure if this fullfils the above math definition). Its reversible and every byte can be changed. But with this it does not enforce that every byte is changed.
EDIT: My solution would be this:
b0 = (a0 ^ a1 ^ a2 ^ a3)
b1 = a1 + b0 ( mod 256)
b2 = a2 + b0 ( mod 256)
b3 = a3 + b0 ( mod 256)
It would be reversible (just subtract the first byte from the other, and then XOR the 3 resulting bytes on the first), and a change in one bit would change every byte (as b0 is the result of all bytes and impacts all others).
Stick all of the bytes into 32-bit number and then do a shl or shr (shift left or shift right) by one, two or three. Then split it back into bytes (could use a variant record). This will move bits from each byte into the adjacent byte.
There are a number of good suggestions here (XOR, etc.) I would suggest combining them.
You could remap the bits. Let's use ii for input and oo for output:
oo[0] = (ii[0] & 0xC0) | (ii[1] & 0x30) | (ii[2] & 0x0C) | (ii[3] | 0x03)
oo[1] = (ii[0] & 0x30) | (ii[1] & 0x0C) | (ii[2] & 0x03) | (ii[3] | 0xC0)
oo[2] = (ii[0] & 0x0C) | (ii[1] & 0x03) | (ii[2] & 0xC0) | (ii[3] | 0x30)
oo[3] = (ii[0] & 0x03) | (ii[1] & 0xC0) | (ii[2] & 0x30) | (ii[3] | 0x0C)
It's not linear, but significantly changing one byte in the input will affect all the bytes in the output. I don't think you can have a reversible transformation such as changing one bit in the input will affect all four bytes of the output, but I don't have a proof.