LYCOS RETRIEVER 
Pseudorandom Number Generator: Sequences
built 784 days ago
Mersenne Twister (MT) is a pseudorandom number generator developed by Makoto Matsumoto and Takuji Nishimura (alphabetical order) during 1996-1997. MT was designed specifically for Monte Carlo simulations, to overcome the flaws found in previous generators. It has far longer period and higher order of equidistribution than other generators: the period is 219937-1 (approximately 4 followed by 6001 zeros), and 623-dimension equidistribution is assured. Period is the number of occurrences before the sequence repeats; the huge period of the MT generator means that for practical purposes, the sequence never repeats. Equidistribution means that every sequence of 623 (or fewer) dice is guaranteed to occur with the correct frequency over the period of the generator. More information may be found on the MT home page.
Source:
A pseudorandom number generator underlies the Java applet you looked at when doing the Project on the Central Limit Theorem. This applet is located at http://www.stat.sc.edu/~west/javahtml/CLT.html and allows you to simulate the rolling of dice. You can use this applet to simulate a coin toss or any experiment where there are equally likely 1/0 outcomes. Simply roll 1 die once and call the roll a success or 1 if the roll is four, five or six and a failure or 0 if the roll is a one, two or three. In this way you can generate a sequence of 0s and 1s.
Source:
In addition, MT2203 pseudorandom number generator is a set of 1024 generators designed to create up to 1024 independent random sequences, which might be used in parallel Monte Carlo simulations. Another generator that has the same feature is Wichmann-Hill. It allows creating up to 273 independent random streams. The properties of the generators designed for parallel computations are discussed in detail in [Coddington94].
Source:
Andrew Yao gave the first convincing definition of a pseudorandom number generator; namely that its output sequences are not distinguishable from those of a truly random generator by any polynomial-time test. He proved that any generator satisfying the next bit test developed by Blum and Micali satisfied his definition, and showed that the discovery of any one-way function would lead to such a pseudorandom generator.
Source:
This is the interface to a simple pseudorandom number generator. Currently this interface is implemented by the RandomLFSR, which uses a linear feedback shift register to generate the sequence and mote address to initialize the register.
Source:
"To the non-specialist, the construction of a random number generator may appear to be the kind of thing that any good programmer can do easily. Over the years many programmers have unwittingly demonstrated that it is all too easy to 'hack' a procedure that will produce a strange looking, apparently unpredictable sequence of numbers. It is fundamentally more difficult... to write quality software which produces what is really desired -- a virtually infinite sequence of statistically independent random numbers, uniformly distributed between 0 and 1. This is a key point: strange and unpredictable is not necessarily random."
Source:
MORE ABOUT
Sequences