Algorithm 89. A procedure realizing a fourth order one-step method for solving a system of ordinary differential equations of the form y''=f(x,y,y')
M. Szyszkowicz (1983)
Applicationes Mathematicae
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M. Szyszkowicz (1983)
Applicationes Mathematicae
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Ladislav Lukšan (1996)
Kybernetika
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M. Szyszkowicz (1983)
Applicationes Mathematicae
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M. Szyszkowicz (1984)
Applicationes Mathematicae
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Evald Übi (2005)
Open Mathematics
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A linear programming problem is transformed to the finding an element of polyhedron with the minimal norm. According to A. Cline [6], the problem is equivalent to the least squares problem on positive ortant. An orthogonal method for solving the problem is used. This method was presented earlier by the author and it is based on the highly developed least squares technique. First of all, the method is meant for solving unstable and degenerate problems. A new version of the artifical basis...
Evald Übi (2007)
Open Mathematics
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The system of inequalities is transformed to the least squares problem on the positive ortant. This problem is solved using orthogonal transformations which are memorized as products. Author’s previous paper presented a method where at each step all the coefficients of the system were transformed. This paper describes a method applicable also to large matrices. Like in revised simplex method, in this method an auxiliary matrix is used for the computations. The algorithm is suitable for...
Mera, Nicolae S. (2005)
Acta Universitatis Apulensis. Mathematics - Informatics
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Ziming Wang, Yiming Xing, Xinghua Zhu (2023)
Kybernetika
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In this paper, we consider the parameter estimation problem for the multivariable system. A recursive least squares algorithm is studied by minimizing the accumulative prediction error. By employing the stochastic Lyapunov function and the martingale estimate methods, we provide the weakest possible data conditions for convergence analysis. The upper bound of accumulative regret is also provided. Various simulation examples are given, and the results demonstrate that the convergence...
Volkmar Friedrich, Bernd Hofmann (1987)
Numerische Mathematik
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