Computational complexity and feasibility of data processing and interval computations
Work detail
The input data for data processing algorithms come from measurements and are hence not precise. We therefore need to estimate the accuracy of the results of data processing. It turns out that even for the simplest data processing algorithms, this problem is, in general, intractable. This book describes for what classes of problems interval computations (i.e. data processing with automatic results verification) are feasible, and when they are intractable. This knowledge is important, e.g. for algorithm developers, because it will enable them to concentrate on the classes of problems for which general algorithms are possible.
Overview
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Contributors
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- Open Author
A. V. Lakeyev
- Open Author
P. T. Kahl
- Open Author
Vladik Kreinovich
- Open Author
J. Rohn
- Open Author
V. Kreinovich
- Open Author
A.V. Lakeyev
- Open Author
P.T. Kahl
- Open Author
Jiri Rohn
- Open Author
Anatoly Lakeyev
- Open Author
Patrick Kahl
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- Image source: Open LibraryCC
Computational Complexity and Feasibility of Data Processing and Interval Computations
- Image source: Open LibraryCC
Computational complexity and feasibility of data processing and interval computations
- Image source: Open LibraryCC
Computational Complexity and Feasibility of Data Processing and Interval Computations (Applied Optimization)
- CCComputational Complexity and Fe...V. Kreinovich, A. V. Lakeyev, J. Rohn, P. T. Kahl
Computational Complexity and Feasibility of Data Processing and Interval Computations