Search results
Results From The WOW.Com Content Network
In computer science, the computational complexity or simply complexity of an algorithm is the amount of resources required to run it. [1] Particular focus is given to computation time (generally measured by the number of needed elementary operations) and memory storage requirements.
In theoretical computer science, the time complexity is the computational complexity that describes the amount of computer time it takes to run an algorithm. Time complexity is commonly estimated by counting the number of elementary operations performed by the algorithm, supposing that each elementary operation takes a fixed amount of time to ...
Here, complexity refers to the time complexity of performing computations on a multitape Turing machine. [1] See big O notation for an explanation of the notation used. Note: Due to the variety of multiplication algorithms, () below stands in for the complexity of the chosen multiplication algorithm.
In computer science, the analysis of algorithms is the process of finding the computational complexity of algorithms—the amount of time, storage, or other resources needed to execute them. Usually, this involves determining a function that relates the size of an algorithm's input to the number of steps it takes (its time complexity ) or the ...
The complexity of an algorithm is usually taken to be its worst-case complexity unless specified otherwise. Analyzing a particular algorithm falls under the field of analysis of algorithms . To show an upper bound T ( n ) {\displaystyle T(n)} on the time complexity of a problem, one needs to show only that there is a particular algorithm with ...
Computational complexity theory deals with how hard computations are, in quantitative terms, both with upper bounds (algorithms whose complexity in the worst cases, as use of computing resources, can be estimated), and from below (proofs that no procedure to carry out some task can be very fast).
In theoretical computer science, the computational complexity of matrix multiplication dictates how quickly the operation of matrix multiplication can be performed. Matrix multiplication algorithms are a central subroutine in theoretical and numerical algorithms for numerical linear algebra and optimization, so finding the fastest algorithm for matrix multiplication is of major practical ...
Algorithmic complexity may refer to: In algorithmic information theory , the complexity of a particular string in terms of all algorithms that generate it. Solomonoff–Kolmogorov–Chaitin complexity , the most widely used such measure.