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Topic: Random number

Related Topics

Random sequence

Pseudorandom number generator

Randomness

Hardware random number generator

Pseudorandom number sequence

Mersenne twister

Random variable

Pseudonoise

Linear congruential generator

Statistical independence

Yarrow algorithm

Blum Blum Shub

Random walk Monte Carlo

Stochastic process

Halton sequences

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	RANDOM.ORG - True Random Number Service
		In reality, most random numbers used in computer programs are pseudo-random, which means they are a generated in a predictable fashion using a mathematical formula.
		This is fine for many purposes, but it may not be random in the way you expect if you're used to dice rolls, roulette wheels and lottery draws.
		The randomness comes from atmospheric noise, which for many purposes is better than the pseudo-random number algorithms typically used in computer programs.
	www.random.org (180 words)

	Random Number -- from Wolfram MathWorld
		A random number is a number chosen as if by chance from some specified distribution such that selection of a large set of these numbers reproduces the underlying distribution.
		Computer-generated random numbers are sometimes called pseudorandom numbers, while the term "random" is reserved for the output of unpredictable physical processes.
		Most random number generators require specification of an initial number used as the starting point, which is known as a "seed." The goodness of random numbers generated by a given algorithm can be analyzed by examining its noise sphere.
	mathworld.wolfram.com /RandomNumber.html (615 words)

	Hardware random number generator at AllExperts
		Random numbers generators can also be obtained from macroscopic phenomena, such as cards, dice, and the roulette wheel.
		There are several informal definitions of randomness, usually based on either a lack of discernible patterns in a sequence, or the unpredictability of the sequence or various aspects of it by, generally, the most puissant possible adversary.
		"Random" numbers are also used for non-gambling purposes, both where their use is mathematically important, such as sampling for opinion polls, and in situations where "fairness" is approximated by randomization, such as selecting jurors and military draft lotteries.
	en.allexperts.com /e/h/ha/hardware_random_number_generator.htm (3891 words)

	RANDOM.ORG - Introduction to Randomness and Random Numbers
		Random numbers are useful for a variety of purposes, such as generating data encryption keys, simulating and modeling complex phenomena and for selecting random samples from larger data sets.
		Random number generators based on quantum physics use the fact that subatomic particles appear to behave randomly in certain circumstances.
		While quantum random number generators can certainly generate true random numbers, it seems to me that they for all intents and purposes are equivalent to approaches based on complex dynamical systems.
	www.random.org /randomness (0 words)

	Random Numbers Info
		A random number generator is a device that produces sequences of numbers complying with the definitions proposed above.
		In applications where pseudo-random numbers are not appropriate, one must resort to using a physical random number generator.
		When designing a random number generator, it is thus a natural choice to take advantage of this intrinsic randomness and to resort to the use of a quantum process as source of randomness.
	www.randomnumbers.info /content/Generating.htm (876 words)

	Dr. Dobb's \| Testing Random Number Generators \| April 15, 2003 (Site not responding. Last check: )
		In each case, the issue is whether, given the number of observations in the subsequence, the computer-generated random numbers appear to be random, or patternless.
		If random numbers from 0 to 100 are equally likely, or equivalently the random numbers are uniformly distributed, the cumulative probability for this theoretical distribution is indicated by the 45-degree line in the figure.
		The random numbers from the generator are mapped into a relatively small number of distinct integer values from 10 to 181.
	www.ddj.com /dept/cpp/184403185 (3707 words)

	Random number
		As the sequence itself had been imposed certain restrictions, the method of choosing the next random element (in the interval defined by restrictions) did not give the random sequence as a whole.
		If we arrange all possible sequences in certain order (for example, in lexicographical order) and assign each sequence its number, after choice of the random number it is possible to take the correspondent sequence for the random one.
		As the amount of sequences is quite large, the number can be a long one, composed of hundreds decimal digits, though our random data generator could give only normal numbers.
	acm.uva.es /p/v5/504.html (0 words)

	Cognitive Daily: Is 17 the "most random" number?
		You're misunderstanding "random." The reason I plotted the computer's random numbers is to show how much variance there is in a set of random numbers the same size as our poll's sample.
		You need to ensure that your random number generator was not using a pseudo random number generator, which would give a predictable order of random numbers every time, given that you know the seed (probably the given time of the sample's creation in milliseconds).
		Random Number Generation is equally likely -no least likely numbers-, independent -your last pick or the last outcome is irrelevant and bears 0 influence on the probabilities of the next outcome- and with replacement -Yes!you will randomly pick the same digit twice once in a while.
	scienceblogs.com /cognitivedaily/2007/02/is_17_the_most_random_number.php (0 words)

	Computer Generated Random Numbers
		Although there is nothing "random" about a completely deterministic computer generated sequence of numbers, we can analyze the sequence of numbers to see if there is any reason to doubt that the sequence could have come from a truly random stochastic process.
		Therefore, a subsequence of a sequence of random numbers is not necessarily random.
		The first random number is used to pick an element from the array of random numbers, and the second random number is used to replace the number chosen.
	world.std.com /~franl/crypto/random-numbers.html (10155 words)

	Take a Chance: Science News Online, Dec. 4, 2004 (Site not responding. Last check: )
		Today, randomness is finding myriad other uses, such as encrypting credit card numbers in Internet transactions, deciding how to allocate treatments in drug trials, choosing precincts to call in national polls, running online gambling sites, and helping physicists simulate phenomena ranging from the weather to traffic patterns.
		A random number is one that can't be predicted.
		These numbers can then be used either as the seeds for computer algorithms or as random numbers in their own right.
	www.sciencenews.org /articles/20041204/bob9.asp (0 words)

	Hardware random number generators
		A hardware random number generator uses a physical phenomenon such as electrical noise from a resistor or semiconductor diode or the decay of a radioactive material for the initial source of randomness.
		The present day hardware random number generators are really too slow for routine use in statistical simulations although it might be very sensible to use them for cross-checking simulations using pseudo-random number generators.
		However, the most important is that the Diehard tests are designed for 32 bit words, whereas hardware random number generators tend to generate their bits one by one and don’t have a 32 bit structure.
	www.robertnz.net /hwrng.htm (0 words)

	Random Numbers \| World of Scientific Discovery
		This will be a random number because it was generated by a random process whose outcome could not be predicted in advance.
		Random numbers are used in casino games, state lotteries, computer games, clinical trials of new drugs, simulations of random walks, encryption techniques, modeling molecular behavior, testing computer programs, and even in computer graphics for rendering realistic-looking images.
		For example, in a large sample of random numbers, each of the ten digits from 0 to 9 should appear about one-tenth of the time.
	www.bookrags.com /research/random-numbers-wsd (0 words)

	pseudo-random number generator (Site not responding. Last check: )
		Hardware-based random number generators are built from parts with naturally random events, such as noise in a diode.
		Using C libraries to get random numbers in a certain range (C) is C FAQ question 13.16.
		Random Number Generation and Testing with links to reports, standard tests, and on-going research.
	www.nist.gov /dads/HTML/pseudorandomNumberGen.html (248 words)

	Boost Random Number Library
		Random numbers are useful in a variety of applications.
		The Boost Random Number Library (Boost.Random for short) provides a vast variety of generators and distributions to produce random numbers having useful properties, such as uniform distribution.
		Several random number generators are available in the following header files; please read the documentation about these.
	www.boost.org /libs/random/index.html (0 words)

	Random number Summary
		In statistics, a random number is a single observation (outcome) of a specified random variable.
		A number itself cannot be random except in the sense of how it was generated.
		Informally, selecting a number at random with uniform distribution on some set requires that all elements of that set were equally probable as outcomes before the selection.
	www.bookrags.com /Random_number (0 words)

	True random number generators
		A hardware (true) random number generator is a piece of electronics that plugs into a computer and produces genuine random numbers as opposed to the pseudo-random numbers that are produced by a computer program such as newran.
		If I used a modern random number generator with vastly more possible values, it would still be difficult to prove that each possible combination of balls had probability close to the theoretical probability.
		So I would really like my hardware random number generator to be as good as possible and the pseudo-random number generator to be used to clean up the very small amount of correlation or bias that remains in the output from the hardware random number generator.
	www.robertnz.net /true_rng.html (0 words)

	Random Number Generation
		There are as many different random number generators as there are ways to search a string for a substring.
		These two random number generators take up very little space, have very long periods and other useful statistical properties, and are extremely fast — much, much faster than the standard random number generator that comes with your platform.
		The Mersenne Twister is a new random number generator, invented/discovered in 1996 by Matsumora and Nishimura.
	www.qbrundage.com /michaelb/pubs/essays/random_number_generation (0 words)

	Wired 11.08: Totally Random
		Random number sequences have been around for 4,000 years, but never have they been in such demand.
		Random numbers also play a crucial role in lotteries and gambling.
		As recently as 100 years ago, people who needed random numbers for scientific work still tossed coins, rolled dice, dealt cards, picked numbers out of hats, or browsed census records for lists of digits.
	www.wired.com /wired/archive/11.08/random.html (0 words)

	Dan's coding practice area, simple programs in various different programming languages
		In Java, the class Random from the package java.util can be used to generated pseudo-random values for a variety of data types, specifically, boolean, byte, int, long, float, and double.
		Internally, all random values generated by objects of this class are produced by calling the method next(int bits) that returns an integer with the requested number of random bits.
		The random seed is left to whatever the default is for the routines used in the respective languages.
	cer.freeshell.org /renma/LibraryRandomNumber (3149 words)

	Random Number Generator Free Download
		Random Number Generator is a Windows based application designed to generate random numbers.Program allow users to do choice lower and upper limits and increment of the numbers.Limits can be positive or negative values.
		User can exclude digits from generated random numbers.Random numbers can be edit and copied to the clipboard for pasting into other applications.
		Random Number Generator will generate to 2500 numbers at the time.
	www.sharewaresoft.com /Random-Number-Generator-download-15111.htm (0 words)

	Random Number Generator Pro for Windows 9x/Me/NT/2000/XP/2003
		User can exclude digits from generated random number.
		Random number can be edit and copied to the clipboard for pasting into other applications.
		Random Number Generator will generate to 9999 numbers at the time.
	www.segobit.com /rng.htm (0 words)

	Random Class (System) (Site not responding. Last check: )
		Represents a pseudo-random number generator, a device that produces a sequence of numbers that meet certain statistical requirements for randomness.
		The chosen numbers are not completely random because a definite mathematical algorithm is used to select them, but they are sufficiently random for practical purposes.
		To generate a cryptographically secure random number suitable for creating a random password, for example, use a class derived from System.Security.Cryptography.RandomNumberGenerator such as System.Security.Cryptography.RNGCryptoServiceProvider.
	msdn2.microsoft.com /en-us/library/system.random.aspx (0 words)

	Random Number (Site not responding. Last check: )
		To generate a vector of random numbers with the same mean and variance, specify the Initial seed parameter as a vector.
		To generate uniformly distributed random numbers, use the Uniform Random Number block.
		Avoid integrating a random signal because solvers are meant to integrate relatively smooth signals.
	www.csb.yale.edu /userguides/datamanip/matlab/help/toolbox/simulink/ref/randomnumber.html (131 words)

	Using and Creating Cryptographic-Quality Random Numbers
		So a number of people got together and decided that if they could find out what the most random number is, they could just use that and lose all those thick books of random numbers.
		For our purposes, a perfectly random number is one that the adversary has to guess, that is that there is no strategy for determining it that is better than brute force.
		Random numbers may be strong or weak (perfectly random numbers are the strongest), and also knowable or unknowable.
	www.merrymeet.com /jon/usingrandom.html (4327 words)

	NERSC Random Number Generators
		Their functionality is approximately the same, but the numbers generated are uniformly distributed greater than or equal to zero and less then one.
		The random numbers are generated using the multiplicative congruential method with a user-specified seed.
		Chapter G05 of the NAG Parallel Library web documentation describes two routines for generating and manipulating random numbers that are unique to the NAG Parallel Library.
	www.nersc.gov /nusers/resources/software/libs/math/random (0 words)

	Digg - Random Number Generation
		The point is that having a weak random number generator is a security weakness.
		Games programmers are happy with predictably random numbers (ie starting with the same seed we always get the same set of random numbers coming back), if our game needs to be fully deterministic and support replays that is.
		To be technical, all random generators aren't 100% random, but those algorithms in the article will give you non-repeating pattern of numbers for a long while before it starts to repeat again.
	digg.com /programming/Random_Number_Generation (0 words)

	>HG324 Random Bit Generator
		Random bits (numbers) produced by HG324 generator pass, with a high probability, any known standard statistical randomness test such as: Frequency test, ChiSquare, Entropy, Autocorrelation test, KS test, picturing randomness and others, as well as the most stringent ones: the Marsaglia's Diehard battery of tests, the Coron's version of Maurer's Universal Statistical Test.
		In either case produced files of 1 000 000 bytes were completely random, according to the ENT battery of standard tests.
		The number of ones should approach number of zeros as the length of the sequence tends to infinity, that is the a priory probability of ones should be equal to 1/2;
	random.com.hr /products/random/hg324.html (1422 words)

	TechXclusives - That is So Random! (Site not responding. Last check: )
		Random numbers are useful for many applications, including security and cryptography.
		Generating a true random number (TRN) with a true random number generator (TRNG) is a difficult task to perform using digital hardware.
		In addition to being able to generate fast streams of true random numbers, you can also test the random number sequences for their properties at the same time they are being generated.
	www.xilinx.com /xlnx/xweb/xil_tx_display.jsp?sGlobalNavPick=&sSecondaryNavPick=&category=&iLanguageID=1&multPartNum=1&sTechX_ID=alsd_random (1097 words)

	Random Number Generator, Random Selection Software and Random Sampling Utilities
		Generate a fixed or variable number of blank data items per set - the position of each blank item is determined at random.
		Use it to generate formatted random numbers: integer and floating point.
		Vortex is a random number generator for integers and floating point numerics.
	www.randombots.com /index.htm (0 words)

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