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If the data is stored on a magnetic tape where seek time depends on the current head position, a tradeoff between longer seek time and more comparisons may lead to a search algorithm that is skewed similarly to Fibonacci search. Fibonacci search is derived from Golden section search, an algorithm by Jack Kiefer (1953) to search for the maximum ...
The usual Fibonacci numbers are a Fibonacci sequence of order 2. The cases n = 3 {\displaystyle n=3} and n = 4 {\displaystyle n=4} have been thoroughly investigated. The number of compositions of nonnegative integers into parts that are at most n {\displaystyle n} is a Fibonacci sequence of order n {\displaystyle n} .
With the exceptions of 1, 8 and 144 (F 1 = F 2, F 6 and F 12) every Fibonacci number has a prime factor that is not a factor of any smaller Fibonacci number (Carmichael's theorem). [56] As a result, 8 and 144 ( F 6 and F 12 ) are the only Fibonacci numbers that are the product of other Fibonacci numbers.
The expansion produced by this method for a number is called the greedy Egyptian expansion, Sylvester expansion, or Fibonacci–Sylvester expansion of . However, the term Fibonacci expansion usually refers, not to this method, but to representation of integers as sums of Fibonacci numbers .
A Lagged Fibonacci generator (LFG or sometimes LFib) 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. The Fibonacci sequence may be described by the recurrence ...
To encode an integer N: . Find the largest Fibonacci number equal to or less than N; subtract this number from N, keeping track of the remainder.; If the number subtracted was the i th Fibonacci number F(i), put a 1 in place i − 2 in the code word (counting the left most digit as place 0).
Moreover, unlike a binary search tree, most of this space is being used to store data: even for billions of elements, the pointers in a full vEB tree number in the thousands. The implementation described above uses pointers and occupies a total space of O(M) = O(2 m), proportional to the size of the key universe. This can be seen as follows.
The golden-section search is a technique for finding an extremum (minimum or maximum) of a function inside a specified interval. For a strictly unimodal function with an extremum inside the interval, it will find that extremum, while for an interval containing multiple extrema (possibly including the interval boundaries), it will converge to one of them.