Autocorrelation, sometimes known as serial correlation in the discrete time case, is the correlation of a signal with a delayed copy of itself as a function of delay. Informally, it is the similarity between observations as a function of the time lag between them. The analysis of autocorrelation is a mathematical tool for finding repeating patterns, such as the presence of a periodic signal obscured by noise, or identifying the missing fundamental frequency in a signal implied by its harmonic frequencies. It is often used in signal processing for analyzing functions or series of values, such as time domain signals.
In mathematics, the Fibonacci numbers, commonly denoted Fn, form a sequence, called the Fibonacci sequence, such that each number is the sum of the two preceding ones, starting from 0 and 1. That is,
A pseudorandom number generator (PRNG), also known as a deterministic random bit generator (DRBG), is an algorithm for generating a sequence of numbers whose properties approximate the properties of sequences of random numbers. The PRNG-generated sequence is not truly random, because it is completely determined by an initial value, called the PRNG's seed. Although sequences that are closer to truly random can be generated using hardware random number generators, pseudorandom number generators are important in practice for their speed in number generation and their reproducibility.
A linear congruential generator (LCG) is an algorithm that yields a sequence of pseudo-randomized numbers calculated with a discontinuous piecewise linear equation. The method represents one of the oldest and best-known pseudorandom number generator algorithms. The theory behind them is relatively easy to understand, and they are easily implemented and fast, especially on computer hardware which can provide modular arithmetic by storage-bit truncation.
The Mersenne Twister is a pseudorandom number generator (PRNG). It is by far the most widely used general-purpose PRNG. Its name derives from the fact that its period length is chosen to be a Mersenne prime.
A Lagged Fibonacci generator is an example of a pseudorandom number generator. This class of random number generator is aimed at being an improvement on the 'standard' linear congruential generator. These are based on a generalisation of the Fibonacci sequence.
In mathematics and computing, Fibonacci coding is a universal code which encodes positive integers into binary code words. It is one example of representations of integers based on Fibonacci numbers. Each code word ends with "11" and contains no other instances of "11" before the end.
In computing, a linear-feedback shift register (LFSR) is a shift register whose input bit is a linear function of its previous state.
In mathematics, a recurrence relation is an equation that recursively defines a sequence or multidimensional array of values, once one or more initial terms of the same function are given; each further term of the sequence or array is defined as a function of the preceding terms of the same function.
Many letters of the Latin alphabet, both capital and small, are used in mathematics, science, and engineering to denote by convention specific or abstracted constants, variables of a certain type, units, multipliers, or physical entities. Certain letters, when combined with special formatting, take on special meaning.
George Marsaglia was an American mathematician and computer scientist. He is best known for creating the diehard tests, a suite of software for measuring statistical randomness.
A randomness test, in data evaluation, is a test used to analyze the distribution of a set of data to see if it can be described as random (patternless). In stochastic modeling, as in some computer simulations, the hoped-for randomness of potential input data can be verified, by a formal test for randomness, to show that the data are valid for use in simulation runs. In some cases, data reveals an obvious non-random pattern, as with so-called "runs in the data". If a selected set of data fails the tests, then parameters can be changed or other randomized data can be used which does pass the tests for randomness.
The Marsaglia polar method is a pseudo-random number sampling method for generating a pair of independent standard normal random variables. While it is superior to the Box–Muller transform, the Ziggurat algorithm is even more efficient.
In computer science, multiply-with-carry (MWC) is a method invented by George Marsaglia for generating sequences of random integers based on an initial set from two to many thousands of randomly chosen seed values. The main advantages of the MWC method are that it invokes simple computer integer arithmetic and leads to very fast generation of sequences of random numbers with immense periods, ranging from around to .
The Lehmer random number generator, sometimes also referred to as the Park–Miller random number generator, is a type of linear congruential generator (LCG) that operates in multiplicative group of integers modulo n. The general formula is:
In sequence design, a Feedback with Carry Shift Register is the arithmetic or with carry analog of a Linear feedback shift register (LFSR). If is an integer, then an N-ary FCSR of length is a finite state device with a state consisting of a vector of elements in and an integer . The state change operation is determined by a set of coefficients and is defined as follows: compute . Express s as with in . Then the new state is . By iterating the state change an FCSR generates an infinite, eventually periodic sequence of numbers in .
A combined linear congruential generator (CLCG) is a pseudo-random number generator algorithm based on combining two or more linear congruential generators (LCG). A traditional LCG has a period which is inadequate for complex system simulation. By combining two or more LCGs, random numbers with a longer period and better statistical properties can be created. The algorithm is defined as:
KISS (Keep it Simple Stupid) is a family of pseudorandom number generators introduced by George Marsaglia. Starting from 1998 Marsaglia posted on various newsgroups including sci.math, comp.lang.c, comp.lang.fortran and sci.stat.math several versions of the generators. All KISS generators combine three or four independent random number generators with a view to improving the quality of randomness. KISS generators produce 32-bit or 64-bit random integers, from which random floating-point numbers can be constructed if desired. The original 1993 generator is based on the combination of a linear congruential generator and of two linear feedback shift-register generators. It has a period 295, good speed and good statistical properties; however, it fails the LinearComplexity test in the Crush and BigCrush tests of the TestU01 suite. A newer version from 1999 is based on a linear congruential generator, a 3-shift linear feedback shift-register and two multiply-with-carry generators. It is 10–20% slower than the 1993 version but has a larger period 2123 and passes all tests in TestU01. In 2009 Marsaglia presented a version based on 64-bit integers (appropriate for 64-bit processors) which combines a multiply-with-carry generator, a Xorshift generator and a linear congruential generator. It has a period of around 2250 (around 1075).
In computational number theory, Marsaglia's theorem connects modular arithmetic and analytic geometry to describe the flaws with the pseudorandom numbers resulting from a linear congruential generator. As a direct consequence, it is now widely considered that linear congruential generators are weak for the purpose of generating random numbers. Particularly, it is inadvisable to use them for simulations with the Monte Carlo method or in cryptographic settings, such as issuing a public key certificate, unless specific numerical requirements are satisfied. Poorly chosen values for the modulus and multiplier in a Lehmer random number generator will lead to a short period for the sequence of random numbers. Marsaglia's result may be further extended to a mixed linear congruential generator.
