prng

In C++11 one can generate numbers with the use of std::random_device with or without a pseudo random number generator like mt19937. What will be the difference using this in this exemplar code: #include <random> #include <iostream> int main() { std::random_device rd; std::mt19937 mt(rd()); std::uniform_real_distribution<double> dist(1, 10); for (int i=0; i<16; ++i) std::cout << dist(rd) << "\t" << dist(mt) << "\n"; } std::random_device is supposed to get you a seed for engines like mt19937 . The quality of successive numbers produced is completely undefined and may easily be insufficient for

I have an implementation of a pseudo random number generator, specifically of George Marsaglia's XOR-Shift RNG. My implementation is here: FastRandom.cs It turns out that the first random sample is very closely correlated with the seed, which is fairly obvious if you take a look at the Reinitialise(int seed) method. This is bad. My proposed solution is to mix up the bits of the seed as follows: _x = (uint)( (seed * 2147483647) ^ ((seed << 16 | seed >> 48) * 28111) ^ ((seed << 32 | seed >> 32) * 69001) ^ ((seed << 48 | seed >> 16) * 45083)); So I have significantly weakened any correlation by

I'm building file-encryption based on AES that have to be able to work in random-access mode (accesing any part of the file). AES in Counter for example can be used, but it is well known that we need an unique sequence never used twice. Is it ok to use a simplified Fortuna PRNG in this case (encrypting a counter with a randomly chosen unique key specific to the particular file)? Are there weak points in this approach? So encryption/decryption can look like this Encryption of a block at Offset: rndsubseq = AESEnc(Offset, FileUniqueKey) xoredplaintext = plaintext xor rndsubseq ciphertext =

I know that it is encouraged to use mt_rand() over rand() because it uses the Mersenne Twister over whatever PRNG rand() uses, but here's something that never seems to be factored in: user activity. In fact, the actions of users can be considered pretty random. For instance, at any given moment, there might be a 4% chance a user might trigger a rand() call for one feature, an 8% chance of a user triggering three rand() calls and a shuffle() , a 20% of a user triggering two rand() calls, and every time a user loads a page the PRNG advances by one. After all, isn't NPC movement what makes RNG

I'm using the WELL512 pseudorandom number generator function described in this paper . The function returns a random unsigned long value. How do I use this return value to produce a random real number within a certain range - like a float between 340.92491 and 859812.53198 inclusive. The documentation for the C rand() function seems to warn against using mod. Nemo Well, mathematically it's just: min_value + (max_value - min_value) * (my_random() / (long double)ULONG_MAX) (Assuming my_random() returns a uniformly distributed number between 0 and ULONG_MAX) However, depending on the exact values

I am writing a kid sister encryption function and I need a PRNG that produces consistent results across OSes (so no floating point math, taking advantage of hardware, or system level software). It would be nice, but not necessary, for the PRNG had a period longer than 2 30 . I am currently using a 32 bit Xorshift : #!/usr/bin/perl use strict; use warnings; { use integer; #use integer math my $x = 123456789; my $y = 362436069; my $w = 88675123; my $z = 521288629; sub set_random_seed { $w = shift; } sub random { my $t = $x ^ ($x << 11); $x = $y; $y = $z; $z = $w; my $rand = $w = ($w ^ ($w >> 19)