Global minimization of a quadratic functional: neural network approach
<|reference_start|>Global minimization of a quadratic functional: neural network approach: The problem of finding out the global minimum of a multiextremal functional is discussed. One frequently faces with such a functional in various applications. We propose a procedure, which depends on the dimensionality of the problem polynomially. In our approach we use the eigenvalues and eigenvectors of the connection matrix.<|reference_end|>
@article{litinskii2004global,
    title={Global minimization of a quadratic functional: neural network approach},
    author={L.B.Litinskii, B.M.Magomedov},
    journal={arXiv preprint arXiv:cs/0412109},
    year={2004},
    number={IONT-04-16},
    archivePrefix={arXiv},
    eprint={cs/0412109},
    primaryClass={cs.NE cs.DM}
}