Time Complexity by Surhone Lambert (23 results)

Taschenbuch. Condition: Neu. Pseudo-Polynomial Time | Computational Complexity Theory, Time Complexity, NP-Complete, NP-Hard | Lambert M. Surhone (u. a.) | Taschenbuch | Englisch | 2026 | OmniScriptum | EAN 9786134709293 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -High Quality Content by WIKIPEDIA articles! In computer science, the time complexity of an algorithm quantifies the amount of time taken by an algorithm to run as a function of the size of the input to the problem. The time complexity of an algorithm is commonly expressed using the big O notation, which suppresses multiplicative constants and lower order terms. When expressed this way, the time complexity is said to be described asymptotically, i.e., as the input size goes to infinity. For example, if the time required by an algorithm on all inputs of size n is at most 5n3 + 3n, the asymptotic time complexity is O(n3).Time complexity is commonly estimated by counting the number of elementary operations performed by the algorithm, where an elementary operation takes a fixed amount of time to perform. Thus the amount of time taken and the number of elementary operations performed by the algorithm differ by at most a constant factor. 92 pp. Englisch.

Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In computational complexity theory, RL (Randomized Logarithmic-space), sometimes called RLP (Randomized Logarithmic-space Polynomial-time), is the complexity class of problems solvable in logarithmic space and polynomial time with probabilistic Turing machines with one-sided error. It is named in analogy with RP, which is similar but has no logarithmic space restriction. The probabilistic Turing machines in the definition of RL never accept incorrectly but are allowed to reject incorrectly less than 1/3 of the time; this is called one-sided error. The constant 1/3 is arbitrary; any x with 0 x 1/2 would suffice. This error can be made 2 p(x) times smaller for any polynomial p(x) without using more than polynomial time or logarithmic space by running the algorithm repeatedly.

Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - High Quality Content by WIKIPEDIA articles! In computational complexity theory, the complexity class NP-complete (abbreviated NP-C or NPC), is a class of problems having two properties: Any given solution to the problem can be verified quickly (in polynomial time); the set of problems with this property is called NP (nondeterministic polynomial time). If the problem can be solved quickly (in polynomial time), then so can every problem in NP. Although any given solution to such a problem can be verified quickly, there is no known efficient way to locate a solution in the first place; indeed, the most notable characteristic of NP-complete problems is that no fast solution to them is known. That is, the time required to solve the problem using any currently known algorithm increases very quickly as the size of the problem grows. As a result, the time required to solve even moderately large versions of many of these problems easily reaches into the billions or trillions of years, using any amount of computing power available today. As a consequence, determining whether or not it is possible to solve these problems quickly is one of the principal unsolved problems in computer science today.

Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. The gift wrapping algorithm is a simple algorithm for computing the convex hull of a given set of points.In the two-dimensional case the algorithm is also known as Jarvis march, after R. A. Jarvis, who published it in 1973; it has O(nh) time complexity, where n is the number of points and h is the number of points on the convex hull. Its real-life performance compared with other convex hull algorithms is favorable when n is small or h is expected to be very small with respect to n. In general cases the algorithm is outperformed by many others.

Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - High Quality Content by WIKIPEDIA articles! The relationship between the complexity classes P and NP is an unsolved question in theoretical computer science. It is considered to be the most important problem in the field. In essence, the question P = NP asks: if 'yes'-answers to a 'yes'-or-'no'-question can be verified 'quickly', can the answers themselves also be computed quickly An answer to the P = NP question would determine whether problems like the subset-sum problem are as 'easy' to compute as to verify. If it turned out P does not equal NP, it would mean that some NP problems are substantially 'harder' to compute than to verify.

Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - High Quality Content by WIKIPEDIA articles! In computational complexity theory, the space hierarchy theorems are separation results that show that both deterministic and nondeterministic machines can solve more problems in (asymptotically) more space, subject to certain conditions. For example, a deterministic Turing machine can solve more decision problems in space n log n than in space n. The somewhat weaker analogous theorems for time are the time hierarchy theorems. The foundation for the hierarchy theorems lies in the intuition that with either more time or more space comes the ability to compute more functions (or decide more languages). The hierarchy theorems are used to demonstrate that the time and space complexity classes form a hierarchy where classes with tighter bounds contain fewer languages than those with more relaxed bounds. Here we define and prove the space hierarchy theorem. The space hierarchy theorems rely on the concept of space-constructible functions.

Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - High Quality Content by WIKIPEDIA articles! In computer science, the time complexity of an algorithm quantifies the amount of time taken by an algorithm to run as a function of the size of the input to the problem. The time complexity of an algorithm is commonly expressed using the big O notation, which suppresses multiplicative constants and lower order terms. When expressed this way, the time complexity is said to be described asymptotically, i.e., as the input size goes to infinity. For example, if the time required by an algorithm on all inputs of size n is at most 5n3 + 3n, the asymptotic time complexity is O(n3).Time complexity is commonly estimated by counting the number of elementary operations performed by the algorithm, where an elementary operation takes a fixed amount of time to perform. Thus the amount of time taken and the number of elementary operations performed by the algorithm differ by at most a constant factor.

Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - High Quality Content by WIKIPEDIA articles! In complexity theory, ZPP (zero-error probabilistic polynomial time) is the complexity class of problems for which a probabilistic Turing machine exists with these properties: It always returns the correct YES or NO answer.; The running time is polynomial on average for any input. In other words, the algorithm is allowed to flip a truly-random coin while it is running. It always returns the correct answer. (Such an algorithm is called a Las Vegas algorithm.) For a problem of size n, there is some polynomial p(n) such that the average running time will be less than p(n), even though it might occasionally be much longer.

Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - High Quality Content by WIKIPEDIA articles! In computer science, polynomial time refers to the running time of an algorithm, that is, the number of computation steps a computer or an abstract machine requires to evaluate the algorithm. An algorithm is said to be polynomial time if its running time is upper bounded by a polynomial in the size of the input for the algorithm. Problems for which a polynomial time algorithm exists belong to the complexity class PTIME, which is central in the field of computational complexity theory. Cobham's thesis states that polynomial time is a synonym for 'tractable', 'feasible', 'efficient', or 'fast'.

Taschenbuch. Condition: Neu. NC (complexity) | Decision Problem, Computational Complexity Theory, Polylogarithmic Time, Parallel Computing | Lambert M. Surhone (u. a.) | Taschenbuch | Englisch | 2026 | OmniScriptum | EAN 9786130992835 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu Print on Demand.

Taschenbuch. Condition: Neu. RL (Complexity) | Computational Complexity Theory, Complexity Class, Logarithmic Space, Polynomial Time, Probabilistic Turing Machine | Lambert M. Surhone (u. a.) | Taschenbuch | Englisch | 2026 | OmniScriptum | EAN 9786131257681 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu Print on Demand.

Taschenbuch. Condition: Neu. NP-easy | Complexity Class, Polynomial Time, Deterministic Turing Machine | Lambert M. Surhone (u. a.) | Taschenbuch | Englisch | 2026 | OmniScriptum | EAN 9783639972634 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu Print on Demand.

Taschenbuch. Condition: Neu. Space Hierarchy Theorem | Computational Complexity Theory, Deterministic Turing Machine, Decision Problem, Time Hierarchy Theorem | Lambert M. Surhone (u. a.) | Taschenbuch | Englisch | 2026 | OmniScriptum | EAN 9786131196027 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu Print on Demand.

Taschenbuch. Condition: Neu. NP-Complete | Computational Complexity Theory, Complexity Class, Polynomial Time, Unsolved Problems in Computer Science, Approximation Algorithm, Subset | Lambert M. Surhone (u. a.) | Taschenbuch | Englisch | 2026 | OmniScriptum | EAN 9786130333287 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu Print on Demand.

Taschenbuch. Condition: Neu. P Versus NP Problem | Complexity Class, Theoretical Computer Science, Decision Problem, Polynomial Time, Subset Sum Problem, Subset | Lambert M. Surhone (u. a.) | Taschenbuch | Englisch | 2026 | OmniScriptum | EAN 9786130335588 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu Print on Demand.

Taschenbuch. Condition: Neu. Time Complexity | Computer Science, Big O Notation, Binary Numeral System, Binary Tree, Parallel Random Access Machine, Frover's Algorithm, Parallel Algorithm | Lambert M. Surhone (u. a.) | Taschenbuch | Englisch | 2026 | OmniScriptum | EAN 9786130552947 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu Print on Demand.

Taschenbuch. Condition: Neu. Gift Wrapping Algorithm | Algorithm, Convex Hull, Time Complexity | Lambert M. Surhone (u. a.) | Taschenbuch | Englisch | 2026 | OmniScriptum | EAN 9786131217692 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu Print on Demand.

Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Please note that the content of this book primarily consists of articlesavailable from Wikipedia or other free sources online. In computerscience, the time complexity of an algorithm quantifies the amount oftime taken by an algorithm to run as a function of the size of the inputto the problem. The time complexity of an algorithm is commonlyexpressed using the big O notation, which suppresses multiplicativeconstants and lower order terms. When expressed this way, the timecomplexity is said to be described asymptotically, i.e., as the inputsize goes to infinity. For example, if the time required by an algorithmon all inputs of size n is at most 5n3 + 3n, the asymptotic timecomplexity is O(n3).Time complexity is commonly estimated by countingthe number of elementary operations performed by the algorithm, where anelementary operation takes a fixed amount of time to perform. Thus theamount of time taken and the number of elementary operations performedby the algorithm differ by at most a constant factor.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 92 pp. Englisch.

Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering.

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Taschenbuch. Condition: Neu. ZPP (Complexity) | Polynomial Time, Turing Machine, Logarithmic Space | Lambert M. Surhone (u. a.) | Taschenbuch | Englisch | 2026 | OmniScriptum | EAN 9786131175589 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu Print on Demand.

Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering.