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  2. Comparison of documentation generators - Wikipedia

    en.wikipedia.org/wiki/Comparison_of...

    Provides warnings if tagged parameters do not match code, parsed parameters included in XML output and Doxygen-style tagfile (-D flag in 8.7). Partial C preprocessor support with -p flag. Support for #if/#ifdef control over documentation inclusion using the -D and -U command-line flags. Imagix 4D: customizable through style sheets and CSS

  3. Random number generation - Wikipedia

    en.wikipedia.org/wiki/Random_number_generation

    Random number generation is a process by which, often by means of a random number generator (RNG), a sequence of numbers or symbols that cannot be reasonably predicted better than by random chance is generated. This means that the particular outcome sequence will contain some patterns detectable in hindsight but impossible to foresee.

  4. Lehmer random number generator - Wikipedia

    en.wikipedia.org/wiki/Lehmer_random_number_generator

    Lehmer random number generator. The Lehmer random number generator[1] (named after D. H. Lehmer), sometimes also referred to as the Park–Miller random number generator (after Stephen K. Park and Keith W. Miller), is a type of linear congruential generator (LCG) that operates in multiplicative group of integers modulo n. The general formula is.

  5. Linear congruential generator - Wikipedia

    en.wikipedia.org/wiki/Linear_congruential_generator

    The second row is the same generator with a seed of 3, which produces a cycle of length 2. Using a = 4 and c = 1 (bottom row) gives a cycle length of 9 with any seed in [0, 8]. A linear congruential generator (LCG) is an algorithm that yields a sequence of pseudo-randomized numbers calculated with a discontinuous piecewise linear equation.

  6. Binary multiplier - Wikipedia

    en.wikipedia.org/wiki/Binary_multiplier

    In binary encoding each long number is multiplied by one digit (either 0 or 1), and that is much easier than in decimal, as the product by 0 or 1 is just 0 or the same number. Therefore, the multiplication of two binary numbers comes down to calculating partial products (which are 0 or the first number), shifting them left, and then adding them ...

  7. Pseudorandom binary sequence - Wikipedia

    en.wikipedia.org/wiki/Pseudorandom_binary_sequence

    A pseudorandom binary sequence (PRBS), pseudorandom binary code or pseudorandom bitstream is a binary sequence that, while generated with a deterministic algorithm, is difficult to predict [1] and exhibits statistical behavior similar to a truly random sequence. PRBS generators are used in telecommunication, such as in analog-to-information ...

  8. Multiply-with-carry pseudorandom number generator - Wikipedia

    en.wikipedia.org/wiki/Multiply-with-carry...

    Thus, a multiply-with-carry generator is a Lehmer generator with modulus p and multiplier b−1 (mod p). This is the same as a generator with multiplier b, but producing output in reverse order, which does not affect the quality of the resultant pseudorandom numbers.

  9. Combined linear congruential generator - Wikipedia

    en.wikipedia.org/wiki/Combined_Linear_Congruenti...

    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. [1] By combining two or more LCGs, random numbers with a longer period and better statistical ...