Topic

# Computation

About: Computation is a research topic. Over the lifetime, 19983 publications have been published within this topic receiving 369340 citations. The topic is also known as: computing.

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01 Jan 2014

TL;DR: This chapter provides an overview of the fundamentals of algorithms and their links to self-organization, exploration, and exploitation.

Abstract: Algorithms are important tools for solving problems computationally. All computation involves algorithms, and the efficiency of an algorithm largely determines its usefulness. This chapter provides an overview of the fundamentals of algorithms and their links to self-organization, exploration, and exploitation. A brief history of recent nature-inspired algorithms for optimization is outlined in this chapter.

8,285 citations

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01 Jan 1989TL;DR: This work discusses parallel and distributed architectures, complexity measures, and communication and synchronization issues, and it presents both Jacobi and Gauss-Seidel iterations, which serve as algorithms of reference for many of the computational approaches addressed later.

Abstract: gineering, computer science, operations research, and applied mathematics. It is essentially a self-contained work, with the development of the material occurring in the main body of the text and excellent appendices on linear algebra and analysis, graph theory, duality theory, and probability theory and Markov chains supporting it. The introduction discusses parallel and distributed architectures, complexity measures, and communication and synchronization issues, and it presents both Jacobi and Gauss-Seidel iterations, which serve as algorithms of reference for many of the computational approaches addressed later. After the introduction, the text is organized in two parts: synchronous algorithms and asynchronous algorithms. The discussion of synchronous algorithms comprises four chapters, with Chapter 2 presenting both direct methods (converging to the exact solution within a finite number of steps) and iterative methods for linear

5,597 citations

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TL;DR: In this article, a convolution-backprojection formula is deduced for direct reconstruction of a three-dimensional density function from a set of two-dimensional projections, which has useful properties, including errors that are relatively small in many practical instances and a form that leads to convenient computation.

Abstract: A convolution-backprojection formula is deduced for direct reconstruction of a three-dimensional density function from a set of two-dimensional projections. The formula is approximate but has useful properties, including errors that are relatively small in many practical instances and a form that leads to convenient computation. It reduces to the standard fan-beam formula in the plane that is perpendicular to the axis of rotation and contains the point source. The algorithm is applied to a mathematical phantom as an example of its performance.

5,356 citations

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TL;DR: In this article, a convolution-backprojection formula is deduced for direct reconstruction of a three-dimensional density function from a set of two-dimensional projections, which has useful properties, including errors that are relatively small in many practical instances and a form that leads to convenient computation.

Abstract: A convolution-backprojection formula is deduced for direct reconstruction of a three-dimensional density function from a set of two-dimensional projections. The formula is approximate but has useful properties, including errors that are relatively small in many practical instances and a form that leads to convenient computation. It reduces to the standard fan-beam formula in the plane that is perpendicular to the axis of rotation and contains the point source. The algorithm is applied to a mathematical phantom as an example of its performance.

5,329 citations

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TL;DR: This experiment demonstrates the feasibility of carrying out computations at the molecular level by solving an instance of the directed Hamiltonian path problem with standard protocols and enzymes.

Abstract: The tools of molecular biology were used to solve an instance of the directed Hamiltonian path problem. A small graph was encoded in molecules of DNA, and the "operations" of the computation were performed with standard protocols and enzymes. This experiment demonstrates the feasibility of carrying out computations at the molecular level.

4,266 citations