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[39] [40] The factorial number system is a mixed radix notation for numbers in which the place values of each digit are factorials. [41] Factorials are used extensively in probability theory, for instance in the Poisson distribution [42] and in the probabilities of random permutations. [43]
The factorial number system is sometimes defined with the 0! place omitted because it is always zero (sequence A007623 in the OEIS). In this article, a factorial number representation will be flagged by a subscript "!". In addition, some examples will have digits delimited by a colon. For example, 3:4:1:0:1:0! stands for
Download QR code; Print/export Download as PDF; ... unlike the factorial, is more broadly defined for all complex numbers other than non-positive integers ...
A natural number is a sociable factorion if it is a periodic point for , where = for a positive integer, and forms a cycle of period . A factorion is a sociable factorion with k = 1 {\displaystyle k=1} , and a amicable factorion is a sociable factorion with k = 2 {\displaystyle k=2} .
Since ! is the product of the integers 1 through n, we obtain at least one factor of p in ! for each multiple of p in {,, …,}, of which there are ⌊ ⌋.Each multiple of contributes an additional factor of p, each multiple of contributes yet another factor of p, etc. Adding up the number of these factors gives the infinite sum for (!
The factorial of a number is ! = (), the product of positive integers up to . Factorial may also refer to: Factorial experiment, a statistical experiment over all combinations of values; Factorial code, data representation by independent components
It is a factorial (7!), the 8th superior highly composite number, [1] the 19th highly composite number, [2] an abundant number, the 8th colossally abundant number [3] and the number of permutations of 4 items out of 10 choices (10 × 9 × 8 × 7 = 5040). It is also one less than a square, making (7, 71) a Brown number pair.
To create factorial codes, Horace Barlow and co-workers suggested to minimize the sum of the bit entropies of the code components of binary codes (1989). Jürgen Schmidhuber (1992) re-formulated the problem in terms of predictors and binary feature detectors , each receiving the raw data as an input.