Prng

PRNG - Pseudorandom number generator, A pseudorandom number generator (PRNG), also known as a deterministic random bit generator (DRBG),[1] is an algorithm for generating a sequence of numbers that approximates the properties of random numbers.

Random

This tag is for questions pertaining to random numbers and their generators, whether pseudo-random or truly random.



Non-random behaviour reflection

Example

"The non-random random behaviour is more a reflection on the quality of the rand prng â it is often not very good"

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PRNG program failure. Cannot enter random amount of choices and will always answer with 2 from the PRNG

"Then you use it as seed in random which is less good that one is a non-cryptographic prng and its output may exhibit some structure which will not register in a statistical measurement tool but might be exploited by an intelligent attacker"

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High quality, simple random password generator

Others

Example

A prng entropy source has much higher quality than what random uses but its entropy source s not guaranteed to be cryptographically secure

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Guid.NewGuid() VS a random string generator from Random.Next()

It s well known that rand is often not a high quality prng pseudo-random number generator but i m a little surprised by this apparently systematic behaviour with seeds that differ by 1 each time;on my mac when i changed srand to srandom and rand to random i got better as in more unpredictable results

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Suggestion about unique values generation

But a large period prng takes up more memory for maintaining the internal state and also takes more time for generating a random number due to complex transitions and post processing

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Random Engine Differences

Rogram output 9 8 4 5 1 10 7 3 6 2 the library s prng is not very random but for many cases that is not important;if program output 9 8 4 5 1 10 7 3 6 2 the library s prng is better algorithms are available

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How can I use the rand() function to generate a different number that hasn't been generated before?

He f#.net journal articles numerical libraries special functions interpolation and random numbers 16th march 2008 and numerical libraries linear algebra and spectral methods 16th april 2008 tested quite a bit of functionality and nmath was actually the slowest of all the commercial libraries;all the commercial libraries prng was slower than all others and 50 slower than the free math.net library some basic functionality was missing the ability to calculate gamma -0.5 and other basic functionality the gamma-related functions all the commercial libraries did provide was broken

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The speed of .NET in numerical computing

It can be simply done by generating random numbers from the range 0 ... 127 and then doing some arithmetic this will likely be faster than invoking prng multiple times

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C++ how do I generate random numbers between -32 to 32 or -64 to 64 and excluding the value zero?

Now the probability that a random value is rejected is guaranteed to be smaller than 50 resulting in a very efficient algorithm just like your bit masking approach;for small bounds the probability that prng is called more than once is extremely small

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Quality of PRNG when not using all bits at once

Hat is where prngs are used to stretch the real entropy to produce more pseudo random numbers from the smaller amount of entropy provided by the trng;the real entropy is used to seed the prng and the prng produces more numbers based on that seed

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How can a pseudorandom number generator possibly be non-repeating?

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