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2019, Volume 2, Issue 2: 83-93. Doi: 10.3934/mfc.2019007

This issue Previous Article Next Article Online learning for supervised dimension reduction

"Reducing the number of dimensions of the possible solution space" as a method for finding the exact solution of a system with a large number of unknowns

1.
Stevana Mokranjca 6, 12000 Požarevac, Serbia
2.
Visoka Tehnička škola strukovnih studija, Njegoseva 2, 12000 Požarevac, Serbia

^* Corresponding author: Aleksa Srdanov
^* Corresponding author: Aleksa Srdanov

Received: February 2019

Revised: March 2019

Published: July 2019

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Abstract

Solving linear systems with a relatively large number of equationsand unknowns can be achieved using an approximate method to obtain a solution with specified accuracy within numerical mathematics. Obtaining theexact solution using the computer today is only possible within the frameworkof symbolic mathematics. It is possible to define an algorithm that does notsolve the system of equations in the usual mathematical way, but still findsits exact solution in the exact number of steps already defined. The methodconsists of simple computations that are not cumulative. At the same time,the number of operations is acceptable even for a relatively large number ofequations and unknowns. In addition, the algorithm allows the process to startfrom an arbitrary initial n-tuple and always leads to the exact solution if itexists.

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Mathematics Subject Classification: Primary: 15A06; Secondary: 65F99.

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References

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