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In computer science, the Fibonacci search technique is a method of searching a sorted array using a divide and conquer algorithm that narrows down possible locations with the aid of Fibonacci numbers. [1] Compared to binary search where the sorted array is divided into two equal-sized parts, one of which is examined further, Fibonacci search ...
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.
Binary, or half-interval, searches repeatedly target the center of the search structure and divide the search space in half. Comparison search algorithms improve on linear searching by successively eliminating records based on comparisons of the keys until the target record is found, and can be applied on data structures with a defined order. [4]
Binary search Visualization of the binary search algorithm where 7 is the target value Class Search algorithm Data structure Array Worst-case performance O (log n) Best-case performance O (1) Average performance O (log n) Worst-case space complexity O (1) Optimal Yes In computer science, binary search, also known as half-interval search, logarithmic search, or binary chop, is a search ...
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Fibonacci numbers are used by some pseudorandom number generators. Fibonacci numbers arise in the analysis of the Fibonacci heap data structure. A one-dimensional optimization method, called the Fibonacci search technique, uses Fibonacci numbers. [74]
Fibonacci search is not faster than binary search, nor is it primarily useful for sorted arrays. It takes log φ n probes in the worst case, more by a factor of 1.44 than the log 2 n probes used by binary search.
In optimization, line search is a basic iterative approach to find a local minimum of an objective function:. It first finds a descent direction along which the objective function f {\displaystyle f} will be reduced, and then computes a step size that determines how far x {\displaystyle \mathbf {x} } should move along that direction.