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- W4379381281 abstract "The paper addresses the construction of an integral model in the form of a quadratic Volterra polynomial based on real-life data corrupted with errors in measurements of the input signal of a dynamic system. The algorithm of polynomial identification is based on the reconstruction of integrals from the Volterra kernels using piecewise constant test signals. The approximation of the integral model is performed by the product integration method generalized to the case of multidimensional convolutions. A smoothing cubic spline is applied to increase the stability of the computational algorithm to measurement noise. The results of a computational experiment in modeling the dynamics of heat engineering equipment in a local section of the steam-water circuit in the power unit of the Nazarovo GRES are presented." @default.
- W4379381281 created "2023-06-06" @default.
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- W4379381281 date "2023-05-15" @default.
- W4379381281 modified "2023-10-12" @default.
- W4379381281 title "Identification of Integral Models of Nonlinear Dynamics by the Product Integration Method with Digital Signal Processing" @default.
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- W4379381281 doi "https://doi.org/10.1109/icieam57311.2023.10138988" @default.
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