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Technical science and innovation

Abstract

The article deals with the construction of algorithms for conditionally optimal filtering of line- ar control systems under the correlation description of external influences. Stable iterative algo- rithms for conditionally optimal filtering are presented for nonparametric description of correlated noise based on the Gauss-Seidel block method for normal equations using the Cholesky decomposi- tion. The reduced stable iterative algorithms of conditionally optimal filtration of linear control sys- tems make it possible to reduce the computational complexity and increase the speed of the iterative process.

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10

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16

References

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