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It is a type of substitution cipher in which each letter in the plaintext is replaced by a letter some fixed number of positions down the alphabet. For example, with a left shift of 3, D would be replaced by A, E would become B, and so on. [1] The method is named after Julius Caesar, who used it in his private correspondence.
An additional problem occurs when the Fisher–Yates shuffle is used with a pseudorandom number generator or PRNG: as the sequence of numbers output by such a generator is entirely determined by its internal state at the start of a sequence, a shuffle driven by such a generator cannot possibly produce more distinct permutations than the ...
In psychology, the transposed letter effect is a test of how a word is processed when two letters within the word are switched.. The phenomenon takes place when two letters in a word (typically called a base word) switch positions to create a new string of letters that form a new, non-word (typically called a transposed letter non-word or TL non-word).
A simple algorithm to generate a permutation of n items uniformly at random without retries, known as the Fisher–Yates shuffle, is to start with any permutation (for example, the identity permutation), and then go through the positions 0 through n − 2 (we use a convention where the first element has index 0, and the last element has index n − 1), and for each position i swap the element ...
Dice are an example of a mechanical hardware random number generator. When a cubical die is rolled, a random number from 1 to 6 is obtained. 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.
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Convert each letter to its natural numerical value, A = 1, B = 2, ..., Z = 26. Generate one keystream value for each letter in the message using the keystream algorithm below. Add each keystream value to the corresponding plaintext number, subtracting 26 if the resulting value is greater than 26. (In mathematics this is called modular arithmetic.)
It can be shown that if is a pseudo-random number generator for the uniform distribution on (,) and if is the CDF of some given probability distribution , then is a pseudo-random number generator for , where : (,) is the percentile of , i.e. ():= {: ()}. Intuitively, an arbitrary distribution can be simulated from a simulation of the standard ...