• Study Resource
  • Explore
    • Arts & Humanities
    • Business
    • Engineering & Technology
    • Foreign Language
    • History
    • Math
    • Science
    • Social Science

    Top subcategories

    • Advanced Math
    • Algebra
    • Basic Math
    • Calculus
    • Geometry
    • Linear Algebra
    • Pre-Algebra
    • Pre-Calculus
    • Statistics And Probability
    • Trigonometry
    • other →

    Top subcategories

    • Astronomy
    • Astrophysics
    • Biology
    • Chemistry
    • Earth Science
    • Environmental Science
    • Health Science
    • Physics
    • other →

    Top subcategories

    • Anthropology
    • Law
    • Political Science
    • Psychology
    • Sociology
    • other →

    Top subcategories

    • Accounting
    • Economics
    • Finance
    • Management
    • other →

    Top subcategories

    • Aerospace Engineering
    • Bioengineering
    • Chemical Engineering
    • Civil Engineering
    • Computer Science
    • Electrical Engineering
    • Industrial Engineering
    • Mechanical Engineering
    • Web Design
    • other →

    Top subcategories

    • Architecture
    • Communications
    • English
    • Gender Studies
    • Music
    • Performing Arts
    • Philosophy
    • Religious Studies
    • Writing
    • other →

    Top subcategories

    • Ancient History
    • European History
    • US History
    • World History
    • other →

    Top subcategories

    • Croatian
    • Czech
    • Finnish
    • Greek
    • Hindi
    • Japanese
    • Korean
    • Persian
    • Swedish
    • Turkish
    • other →
 
Profile Documents Logout
Upload
Optimal Efficiency Guarantees for Network Design Mechanisms*
Optimal Efficiency Guarantees for Network Design Mechanisms*

On Lattices, Learning with Errors, Random Linear Codes, and
On Lattices, Learning with Errors, Random Linear Codes, and

pptx
pptx

A New Discontinuous Petrov-Galerkin Method with Optimal Test
A New Discontinuous Petrov-Galerkin Method with Optimal Test

... of Brooks and Hughes [6], which biases the standard test function by some amount in the direction of convection. SUPG is still the most popular FEM stabilization method to date. Discontinuous Galerkin (DG) methods form a subclass of FEM; first introduced by Reed and Hill in [22], these methods were ...
On the Repairman Problem with Controlled Servers and Switch
On the Repairman Problem with Controlled Servers and Switch

Transportation problem
Transportation problem

ppt - Department of Mathematics | University of Washington
ppt - Department of Mathematics | University of Washington

38. A preconditioner for the Schur complement domain
38. A preconditioner for the Schur complement domain

Computing intersections in a set of line segments: the Bentley
Computing intersections in a set of line segments: the Bentley

Timing Optimization During the Physical Synthesis of
Timing Optimization During the Physical Synthesis of

... must be properly handled by synthesis tools. This thesis focuses on techniques for timing closure of cellbased VLSI circuits, i.e. techniques able to iteratively reduce the number of timing violations until the synthesis of the synchronous digital system reaches the specified target frequency. The d ...
Availability-aware Mapping of Service Function Chains
Availability-aware Mapping of Service Function Chains

Streaming algorithms for embedding and computing edit distance in
Streaming algorithms for embedding and computing edit distance in

STP A Decision Procedure for Bit
STP A Decision Procedure for Bit

Waring`s Problem: A Survey
Waring`s Problem: A Survey

pdf
pdf

Version 2
Version 2

mohammad.ghoniem.info
mohammad.ghoniem.info

Memoizing Top-Down Backtracking Left
Memoizing Top-Down Backtracking Left

pdf
pdf

Undecidability of the unification and admissibility problems for
Undecidability of the unification and admissibility problems for

High Stakes: Gambling, Depression and Suicide
High Stakes: Gambling, Depression and Suicide

Shortest Paths in Directed Planar Graphs with Negative Lengths: a
Shortest Paths in Directed Planar Graphs with Negative Lengths: a

... O(log n) times (rather than once, as in Dijkstra’s algorithm) and many arcs can be relaxed at once. A central concept of the algorithm of Fakcharoenphol and Rao is the dense distance graph. This consists of a recursive decomposition of a graph using separators, together with a table for each subgrap ...
Design of Cognitive Radio Systems Under Temperature
Design of Cognitive Radio Systems Under Temperature

Marginal Bidding: An Application of the Equimarginal Principle to
Marginal Bidding: An Application of the Equimarginal Principle to

book here
book here

< 1 2 3 4 5 6 7 8 9 ... 53 >

Computational complexity theory



Computational complexity theory is a branch of the theory of computation in theoretical computer science and mathematics that focuses on classifying computational problems according to their inherent difficulty, and relating those classes to each other. A computational problem is understood to be a task that is in principle amenable to being solved by a computer, which is equivalent to stating that the problem may be solved by mechanical application of mathematical steps, such as an algorithm.A problem is regarded as inherently difficult if its solution requires significant resources, whatever the algorithm used. The theory formalizes this intuition, by introducing mathematical models of computation to study these problems and quantifying the amount of resources needed to solve them, such as time and storage. Other complexity measures are also used, such as the amount of communication (used in communication complexity), the number of gates in a circuit (used in circuit complexity) and the number of processors (used in parallel computing). One of the roles of computational complexity theory is to determine the practical limits on what computers can and cannot do.Closely related fields in theoretical computer science are analysis of algorithms and computability theory. A key distinction between analysis of algorithms and computational complexity theory is that the former is devoted to analyzing the amount of resources needed by a particular algorithm to solve a problem, whereas the latter asks a more general question about all possible algorithms that could be used to solve the same problem. More precisely, it tries to classify problems that can or cannot be solved with appropriately restricted resources. In turn, imposing restrictions on the available resources is what distinguishes computational complexity from computability theory: the latter theory asks what kind of problems can, in principle, be solved algorithmically.
  • studyres.com © 2025
  • DMCA
  • Privacy
  • Terms
  • Report