Tag: computational complexity
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Big Thetha
Big Θ (Theta) notation is a mathematical concept used to describe the tight bound of an algorithm’s performance. Unlike Big O, which focuses on the worst-case scenario, or Big Ω, which captures the best-case scenario, Big Θ provides a precise measure of the algorithm’s growth rate by considering both upper and lower bounds. It essentially…
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Big Omega
Big Ω (Omega) notation is a mathematical concept used to describe the best-case performance of an algorithm. It provides a lower bound on the running time or space required by an algorithm as a function of the input size . In simpler terms, Big Ω defines the minimum time an algorithm will take, regardless of…
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Big o notation
Big O Notation is a mathematical concept widely used in computer science to describe the efficiency and scalability of algorithms. It provides a framework to evaluate how the runtime or space requirements of an algorithm grow relative to the size of the input data. By abstracting away hardware and implementation specifics, Big O focuses on…
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Undecidability and Turing Machines in Computational theory
Undecidability is a fundamental concept in theoretical computer science, particularly in the study of computational theory and Turing machines. It refers to the class of problems for which no algorithm exists that can determine the answer in a finite amount of time for all possible inputs. These problems are “undecidable” because they cannot be solved…