| Цитирование: | 1. Alefeld, G., Herzberger, J.: Introduction to Interval Computations. Academic Press, New York (1983)
2. Beeck, H.: Über die Struktur und Abschätzungen der Lösungsmenge von linearen Gleichungssystemen mit Intervallkoeffizienten. Computing 10, 231–244 (1972)
3. Draper, N.R., Smith, H.: Applied Regression Analysis, 3rd edn. Wiley, New York (1998)
4. Fiedler, M., Nedoma, J., Ramik, J., Rohn, J., Zimmerman, M.: Linear Optimization Problems with Inexact Data. Springer, Berlin (2006)
5. Jaulin, L., Kieffer, M., Didrit, O., Walter, E.: Applied Interval Analysis, with Examples in Parameter and State Estimation. Robust Control and Robotics. Springer, London (2001)
6. Kantorovich, L. V.: On some new approaches to numerical methods and processing observation data. Sib. Math. J. 3(5), 701–709 (1962) (in Russian). Electronic version is accessible at http://www.nsc.ru/interval/Introduction/Kantorovich62.pdf
7. Kearfott, R.B., Nakao, M., Neumaier, A., Rump, S., Shary, S.P., van Hentenryck, P.: Standardized notation in interval analysis. Comput. Technol. 15(1), 7–13 (2010)
8. Kurzhanski, A.B., Vályi, I.: Ellipsoidal Calculus for Estimation and Control. Birkhäuser, Boston (1996)
9. Lakeyev, A.V., Noskov, S.I.: A description of the set of solutions of a linear equation with intervally defined operator and right-hand side. Russian Acad. Sci. Dokl. Math. 47(3), 518–523 (1993)
10. Milanese, M., Norton, J., Piet-Lahanier, H., Walter, E. (eds.): Bounding Approaches to System Identification. Plenum Press, New York (1996)
11. Moore, R.E., Kearfott, R.B., Cloud, M.J.: Introduction to Interval Analysis. SIAM, Philadelphia (2009)
12. Neumaier, A.: Interval Methods for Systems of Equations. Cambridge University Press, Cambridge (1990)
13. Nurminski, E.A.: Separating plane algorithms for convex optimization. Math. Progr. 76(3), 373–391 (1997)
14. Rao, C.R., Toutenburg, H., Shalabh, Heumann, C.: Linear Models and Generalizations. Least Squares and Alternatives. Springer, New York (2008)
15. Remez, E.Ya.: General computational methods of Chebyshev approximation: The problems with linear real parameters. Oak Ridge, U.S. Atomic Energy Commission. Translation 4491 (1962)
16. Schweppe, F.C.: Recursive state estimation: unknown but bounded errors and system inputs. IEEE Trans. Autom. Control 13(1), 22–28 (1968)
17. Shary, S.P.: Solvability of interval linear equations and data analysis under uncertainty. Autom. Remote Control 73(2), 310–322 (2012). doi:10.1134/S0005117912020099
18. Shary, S.P.: Finite-dimensional interval analysis. Institute of Computational Technologies SB RAS, Novosibirsk (2013). Electronic book accessible at http://www.nsc.ru/interval/Library/InteBooks
19. Shary, S.P., Sharaya, I.A.: Recognition of solvability of interval equations and its application to data analysis. Comput. Technol. 18(3), 80–109 (2013) (in Russian)
20. Shary, S.P., Sharaya, I.A.: On solvability recognition for interval linear systems of equations. Optim. Lett. (2015). Prepublished on May 6, 2015. doi: 10.1007/s11590-015-0891-6
21. Shor, N.Z.: Nondifferentiable Optimization and Polynomial Problems. Kluwer, Boston (1998)
22. Shor, N.Z., Stetsyuk, P.I.: Modified r -algorithm to find the global minimum of polynomial functions. Cybern. Syst. Anal. 33(4), 482–497 (1997)
23. Strekalovsky, A.S.: On the minimization of the difference of convex functions on a feasible set. Comput. Math. Math. Physics 43(3), 380–390 (2003)
24. Vorontsova, E.A.: A projective separating plane method with additional clipping for non-smooth optimization. WSEAS Trans. Math. 13, 115–121 (2014)
25. Zhilin, S.I.: On fitting empirical data under interval error. Reliab. Comput. 11(5), 433–442 (2005)
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