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A random seed (or seed state, or just seed) is a number (or vector) used to initialize a pseudorandom number generator. A pseudorandom number generator's number sequence is completely determined by the seed: thus, if a pseudorandom number generator is later reinitialized with the same seed, it will produce the same sequence of numbers.
The list of widely used generators that should be discarded is much longer [than the list of good generators]. Do not trust blindly the software vendors. Check the default RNG of your favorite software and be ready to replace it if needed. This last recommendation has been made over and over again over the past 40 years.
Noam Nisan (1992) showed that this derandomization can actually be achieved with a pseudorandom generator of seed length () that fools all ()-space machines. Nisan's generator has been used by Saks and Zhou (1999) to show that probabilistic log-space computation can be simulated deterministically in space O ( log 1.5 n ...
While /dev/urandom is still intended as a pseudorandom number generator suitable for most cryptographic purposes, the authors of the corresponding man page note that, theoretically, there may exist an as-yet-unpublished attack on the algorithm used by /dev/urandom, and that users concerned about such an attack should use /dev/random instead. [7]
Default generator in R and the Python language starting from version 2.3. Xorshift: 2003 G. Marsaglia [26] It is a very fast sub-type of LFSR generators. Marsaglia also suggested as an improvement the xorwow generator, in which the output of a xorshift generator is added with a Weyl sequence.
Get shortened URL; Download QR code; ... ACORN (random number generator) ... R. Random number generator attack; Random seed; RANDU;
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If you segment the N bits of data into every possible word of length k, you will be able to list every possible combination of 0s and 1s for a k-bit binary word, with the exception of the all-0s word. [4]: §2 For example, PRBS3 = "1011100" could be generated from + +. [6]