Центр оптико-нейронных технологий
ФГУ ФНЦ НИИСИ РАН
НИИСИ РАН
Структура
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Контакты
• Ассоциация нейроинформатики
• Конференция НЕЙРОИНФОРМАТИКА
Журналы:
• Нейроинформатика
• Optical Memory and Neural Networks


Крыжановский Борис Владимирович

Список публикаций посвещенных нейросетям


  1. Boris Kryzhanovsky and Magomed Malsagov. Investigation of the spectrum of local minima in the spin-glass models. Optical Memory and Neural Networks (Information Optics), vol.25, No.1, pp.1-15, 2016.http://arxiv.org/abs/1606.02457

  2. Boris Kryzhanovsky and Leonid Litinskii. n-Vicinities Method for Three Dimensional Ising Model. Journal of Physics: Conference Series 738 (2016) 012064.http://arxiv.org/abs/1606.09034

  3. A. Igityan, Y. Kafadaryan, N. Aghamalyan, S. Petrosyan, G. Badalyan, V. Vardanyan, M. Nersisyan, R. Hovsepyan, A. Palagushkin, B. Kryzhanovsky. Resistivity switching properties of Li-doped ZnO films deposited on LaB6 electrode. Thin Solid Films, Vol. 595, Part A, Pages 92–95 (2015).

  4. Boris Kryzhanovsky and Leonid Litinskii. Approximate method of free energy calculation for spin system with arbitrary connection matrix. J. Phys.: Conf. Ser. 574, 012017 (2015).

  5. I.M. Karandashev and B.V. Kryzhanovsky. Matrix Transformation Method in Quadratic Binary Optimization. Optical Memory and Neural Networks (Information Optics), vol.24 , No.2, pp.67-81, 2015.

  6. Boris Kryzhanovsky and Leonid Litinskii. Generalized approach to description of energy distribution of spin system. Optical Memory and Neural Networks (Information Optics), vol.24, No.3, pp.165-185, 2015. arXiv:1505.03393

  7. A.O. Melikyan, B.V. Kryzhanovsky. Modeling of the optical properties of silver with use of six fitting parameters. Optical Memory and Neural Networks (Information Optics), vol.23, No.1, pp.1-5 , 2014.

  8. I.M. Karandashev, B.V. Kryzhanovsky. Attraction Area of Minima in Quadratic Binary Optimization. Optical Memory and Neural Networks (Information Optics), vol.23 , No.2, pp.84-88, 2014.

  9. Boris Kryzhanovsky and Leonid Litinskii. Approximate method оf free energy calculation for spin system with arbitrary connection matrix. International Conference on Mathematical Modeling in Physical Sciences IC-MSQUARE, August 28-31, 2014, Madrid, Spain.

  10. B. Kryzhanovsky, L. Litinskii. Approximate method оf free energy calculation for spin system with arbitrary connection matrix. ArXiv 1410.6696

  11. Iakov Karandashev and Boris Kryzhanovsky. Mix-Matrix Transformation Method for Max-Cut Problem. ICANN, Lecture Notes in Computer Science, Vol. 8681, p.323 (2014).

  12. B. Kryzhanovsky, L. Litinskii. Generalized Bragg-Williams Equation for System with an Arbitrary Long-Range Interaction. Doklady Mathematics, Vol. 90, No. 3, pp. 784–787 (2014).

  13. I.M. Karandashev and B.V. Kryzhanovsky. Increasing the attraction area of the global minimum in the binary optimization problem. // Journal of Global Minimization, Vol. 56, Issue 3 (2013), Page 1167-1185.

  14. Eyal Cohen, Shlomi Dolev, Sergey Frenkel, Boris Kryzhanovsky, Alexandr Palagushkin, Michael Rosenblit, and Victor Zakharov. Optical solver of combinatorial problems: nanotechnological approach. JOSA A Vol. 30, Iss. 9, pp. 1845–1853 (2013). http://arxiv.org/abs/1205.0040v1.

  15. B.V. Kryzhanovsky, A.N. Palagushkin, S.A. Prokopenko, A.P. Sergeev and A.O. Melikyan. Controlling Reflectivity of Silver-Corundum-Silver Nanostructure by DC Voltage. Optical Memory and Neural Networks (Information Optics), vol.22, No.1, pp. 1-7, 2013.

  16. Iakov Karandashev, Boris Kryzhanovsky and Leonid Litinskii. Weighted patterns as a tool to improve the Hopfield model. // Physical Review E 85, 041925 (2012) .

  17. B.V. Kryzhanovsky, A.N. Palagushkin, S.A. Prokopenko, A.P. Sergeev and A.O. Melikyan. Drastic Changes in Dielectric Function of Silver Under dc Voltage.http://arxiv.org/abs/1204.6400

  18. B.V. Kryzhanovskii, A.O. Melikyan, A.N. Palagushkin, S.A. Prokopemko, and A.P. Sergeev. Effect of the Electric Field on Optical Parameters of a Metal–Dielectric–Metal Nanostructure. Doklady Physics, 2012, Vol. 57, No. 9, pp. 331–334, 2012.

  19. I. Karandashev, B. Kryzhanovsky, L. Litinskii. Elimination of a catastrophic destruction of a memory in the Hopfield model. Proc. of 13th International Conference on Engineering Applications of Neural Networks, EANN-2012, London. Communications in Computer and Information Science, vol.311, pp.1-10, Springer.

  20. I. Karandashev, B. Kryzhanovsky, L. Litinskii. Properties of the Hopfield Model with Weighted Patterns. ICANN-2012, Losanna // Lecture Notes in Computer Science, vol. 7552, Part I, pp. 41-48 (2012). Springer Berlin/Heidelberg.

  21. I. Karandashev, B. Kryzhanovsky. The Mix-matrix Method in the Problem of Binary Quadratic Optimization. ICANN-2012, Losanna // Lecture Notes in Computer Science, vol. 7552, Part I, pp. 9-16 (2012). Springer Berlin/Heidelberg.

  22. Iakov Karandashev and Boris Kryzhanovsky. Mix-matrix Method in the Problem of Discrete Optimization. ICCGI 2012, VII International Multi-Conference on Computing in the Global Information Technology. Italy. Proc. of ICCGI-2012, pp.218-224. ISBN: 978-1-61208-202-8

  23. Ya.M. Karandashev, B.V. Kryzhanovsky, L.B. Litinskii. Strong Instability of the Minima Spectrum of a Quadratic Binary Functional. Doklady Mathematics, 2011, Vol. 83, No. 1, pp. 116–120.

  24. B.V. Kryzhanovsky, M.V. Kryzhanovsky, M.Yu. Malsagov. Discretization of a Matrix in Quadratic Functional Binary Optimization. Doklady Mathematics, Vol. 83, No.3, pp.413-417 (2011).http://arxiv.org/abs/1205.0732

  25. I.M. Karandashev and B.V. Kryzhanovsky. Transformation of Edge Weights in Graph Bipartition Problem. ICANN-2011. Lecture Notes in Computer Science 6792, pp. 25–31, 2011.

  26. I.M. Karandashev and B.V. Kryzhanovsky. Increasing the attraction area of the global minimum in the binary optimization problem.http://arxiv.org/abs/1109.0165

  27. I.M. Karandashev and B.V. Kryzhanovsky. Transformation of edge weights in a graph bipartitioning problem. // Lecture Notes in Computer Science. Springer Berlin/Heidelberg , vol. 6792, pp. 25-31 (2011).

  28. Iakov Karandashev, Boris Kryzhanovsky and Leonid Litinskii. Hopfield-type memory without catastrophic forgetting. In: FUTURE COMPUTING 2011: III International Conference on Future Computational Technologies and Applications, pp. 57-61. © IARIA, 2011, ISBN: 978-1-61208-154-0.

  29. B. Kryzhanovsky, V. Kryzhanovskiy, L.Litinskii. Machine Learning in Vector Models of Neural Networks. // Advances in Machine Learning II. (J.Koronacki et al. Eds.). Springer. ISSN: 1860-949X ,Vol. 263/2010, pp.427-443 (2010).

  30. B.V. Kryzhanovsky, V.M. Kryzhanovsky. The Binarization of the Decision Rule in the Binary Optimization Problem. // ISSN 1060-992X, Optical Memory and Neural Networks (Information Optics), 2010, Vol. 19, No. 1, pp. 13–22. © Allerton Press, Inc., 2010.

  31. Boris Kryzhanovsky and Leonid Litinskii. Investigation of Generalized Hopfield Model by Statistical Physics Methods. 2010 IEEE World Congress on Computation Intelligance – IJCNN, pp.2480-24-85. Barcelona-2010. ISBN: 978-1-4244-6917-8.

  32. Ya.M. Karandashev, B.V. Kryzhanovsky. Efficient Energy Landscape Transformation in the Problem of Binary Minimization. 2010 IEEE World Congress on Computation Intelligance – IJCNN, pp.1750-1755. Barcelona-2010. ISBN: 978-1-4244-6917-8.

  33. Ya.M. Karandashev, B.V. Kryzhanovsky. Efficient Increasing of Global Minimum Basin of Attraction. Optical Memory and Neural Networks, vol. 19, No.2 , pp. 110-125 (2010).

  34. Y. Karandashev, B. Kryzhanovsky, L. Litinskii. Local Minima of a Quadratic Binary Functional with a Quasi-Hebbian Connection Matrix. Lecture Notes in Computer Science, Springer Berlin / Heidelberg , Vol. 6354, pp. 41-51, 2010.

  35. Y. Karandashev, B. Kryzhanovsky. Binary minimization: Increasing the attraction area of the global minimum in the binary optimization problem. Lecture Notes in Computer Science, Springer Berlin / Heidelberg , Vol. 6353, pp. 525-530, 2010.

  36. B.V. Kryzhanovsky, V.M. Kryzhanovsky. The shape of a local minimum and the probability of its detection in random search. Lecture Notes in Electrical Engineering. Filipe, Joaquim; Ferrier, Jean-Louis; Andrade-Cetto, Juan (Eds.) Vol. 24, pp.51-61 (2009). ISBN: 978-3-540-85639-9.

  37. B.V. Kryzhanovsky, D.I. Simkina, V.M. Kryzhanovsky. A Vector Model of Associative Memory with Clipped Synapses. Pattern Recognition and Image Analysis, vol.19, №2, p. 289-295 (2009).

  38. B.V. Kryzhanovsky, V.M. Kryzhanovsky. An Accelerated Procedure for Solving Binary Optimization Problems. // ISSN 1064-2307, Journal of Computer and Systems Sciences International, 2009, Vol. 48, No. 5, pp. 732–738. © Pleiades Publishing, Ltd., 2009.

  39. Y.M. Karandashev, B.V. Kryzhanovsky. Transformation of Energy Landscape in the Problem of Binary Minimization. Doklady Mathematics, v.80, No.3, pp.927-931 (2009).

  40. B.V. Kryzhanovsky. Expansion of a matrix in terms of external products of configuration vectors. Optical Memory and Neural Networks, vol.17, No.1, pp.62-68 (2008).

  41. Boris Kryzhanovsky, Vladimir Kryzhanovsky. Binary optimization: On the probability of a local minimum detection in random search. Lecture Notes in Computer Science, Artificial Intelligence and Soft Computing – ICAISC 2008. LNAI 5097/2008, pp.89-100. Springer Berlin / Heidelberg ISSN 0302-9743.

  42. Vladimir Kryzhanovsky, Boris Kryzhanovsky. Application of Potts-model Perceptron for Binary Patterns Identification. Lecture Notes in Computer Science, Springer Berlin / Heidelberg , Vol. 5163/2008, pp.553-561.

  43. V.M. Kryzhanovsky. Modified q-state Potts Model with Binarized Synaptic Coefficients. Lecture Notes in Computer Science, Springer Berlin / Heidelberg , Vol. 5164/2008, pp.72-80.

  44. B.V. Kryzhanovsky, V.M. Kryzhanovsky. Distinguishing Features of a Small Hopfield Model with Clipping of Synapses. Optical Memory and Neural Networks, v.17, No.3, pp. 193-200 (2008).

  45. B.V. Kryzhanovsky, V.M. Kryzhanovsky. A Binary Pattern Classification Using Potts Model. Optical Memory & Neural Networks, v/17, No. 4, pp.308-316 (2008).

  46. B.V. Kryzhanovsky. Shape of a Local Minimum and Probability of Its Detection in the Binary Optimization Problem. Differential Equations, vol.44, pp.1188-1190 (2008).

  47. B.V. Kryzhanovskii, V.M. Kryzhanovskii, A.L. Mikaelyan. Application of the clipping procedure to the binary minimization of a quadratic functional. Doklady Mathematics, Volume 75, No2 , pp. 310-313, 2007. (ISSN 1064-5624)

  48. B.V. Kryzhanovsky, V.M. Kryzhanovsky, A.L. Mikaelian. Binary optimization: A relation between the depth of a local minimum and the probability of its detection. 4th International Conference on Informatics in Control, Automation and Robotics. pp.5-10. ICINCO 2007, Anger, France.

  49. B.V. Kryzhanovsky, M.V. Kryzhanovsky, A.L. Mikaelian. New accelerated algorithm based on domain neural network for solving optimization tasks. Optical Memory and Neural Networks, vol.16, No.1, pp.31-39, 2007.

  50. B.V. Kryzhanovsky, M.V. Kryzhanovsky, V.M. Kryzhanovsky. Correlation between the gradients of the quadratic functional and its clipped prototype. Optical Memory and Neural Networks, vol.16, No.4, pp.227-233, 2007.

  51. B.V. Kryzhanovsky, B.M. Magomedov, A.B. Fonarev. Binary optimization: A relation between the depth of a local minimum and the probability of its detection. Optical Memory and Neural Networks, vol.15, No.4, pp.170-179 (2006).

  52. Boris Kryzhanovsky, Bashir Magomedov. Domain Dynamics in Optimization Tasks. Lecture Notes in Computer Science. Publisher: Springer Berlin / Heidelberg ISSN: 0302-9743 Volume 4029 / 2006 , pp.37-45 (2006).

  53. Boris Kryzhanovsky, Bashir Magomedov. Domain Dynamics in Optimization Tasks. Lecture Notes in Computer Science. Publisher: Springer Berlin / Heidelberg ISSN: 0302-9743 Volume 4029 / 2006 , pp.37-45 (2006).

  54. B.V. Kryzhanovsky, B.M. Magomedov, A.B. Fonarev. On the Probability of Finding Local Minima in Optimization Problems. Proc. of International Joint Conference on Neural Networks IJCNN-2006, pp.5888-5892. Vancouver, Canada.

  55. D.I. Alieva, B.V. Kryzhanovsky, V.M. Kryzhanovsky, A.B. Fonarev. Q-valued neural network as a system of fast indentification and pattern recognition. Pattern Recognition and Image Analysis, Vol.15, №1, pp. 30-33, (2005).

  56. B.V. Kryzhanovsky, L.B. Litinskii. Vector neuron models of associative memory for pattern recognition. Pattern Recognition and Image Analysis, Vol.15, №1, pp.69-71, (2005).

  57. B.V. Kryzhanovsky, B.M. Magomedov, A.L. Mikaelian. A Domaine Model of Neural Network. Doklady Mathematics, vol.71, N2, pp.310-314 (2005).

  58. B.V. Kryzhanovskii, B.M. Magomedov, and A.L. Mikaelyan. A Relation Between the Depth of a Local Minimum and the Probabilityof Its Detection in the Generalized Hopfield Model. Doklady Mathematics, vol.72, N3, pp. 986-990 (2005).

  59. A.L. Mikaelian, B.V. Kryzhanovsky, A.N. Palagushkin et al. Sensors Using Plasmon Nanostructures. Optical Memory&Neural Network, vol. 14 , No.4 , pp. 229-244, 2005.

  60. B.V. Kryzhanovsky, V.M. Kryzhanovsky, A.L. Mikaelian and A.B. Fonarev. Parametrical Neural Network For Binary Patterns Identification. Optical Memory&Neural Network, vol. 14 , No.2 , pp. 81-90, 2005.

  61. M.V. Kryzhanovsky, B.V. Kryzhanovsky, A.L. Mikaelian and A.B. Fonarev. Neural-network approach to the target assignment problem in multyagent system. Optical Memory&Neural Network vol. 14 , No.4 , pp. 209-214, 2005.

  62. B.V. Kryzhanovsky, V.M. Kryzhanovsky, A.B. Fonarev. Decorrelating Parametrical Neural Network. Proc. of IJCNN Montreal-2005, pp.1023-1026.

  63. Boris Kryzhanovsky, Bashir Magomedov. Application of domain neural network to optimization tasks. Proc. of XVII International Conf. on Artificial Neuarl Natworks, ICANN 2005. Poland, Warsaw. W. Duch et al (Eds): LNCS 3697, Part II, pp.397-403. Springer-Verlag Berlin 2005.

  64. Boris Kryzhanovsky and Bashir Magomedov. Application of Domain Neural Network to Optimization Tasks. Lecture Notes in Computer Science, vol. 3697/2005, pp. 397-403, 2005.

  65. B.V. Kryzhanovsky, L.B. Litinskii, A.L. Mikaelian. Vector-neuron models of associative memory. Proc. of Int. Joint Conference on Neural Networks IJCNN-04, Budapest-2004, pp.909-1004, 2004.

  66. B.V. Kryzhanovsky, A.L. Mikaelian and A.B. Fonarev. VECTOR NEURAL NET IDENTIFING MANY STRONGLY DISTORTED AND CORRELATED PATTERNS. Int. conf on Information Optics and Photonics Technology, Photonics Asia-2004, Beijing-2004. Proc. of SPIE, vol. 5642 (SPIE, Bellingham, WA 2005), pp. 124-133.

  67. B.V. Kryzhanovsky, V.M. Kryzhanovsky, B.M. Magomedov and A.L. Mikaelian. VECTOR PERCEPTRON AS FAST SEARCH ALGORITHM. Optical Memory&Neural Network, vol.13, No.2, pp.103-108, 2004.

  68. Б.В. Крыжановский, А.Л. Микаэлян. Ассоциативная память, способная распознавать сильно скоррелированные образы. Доклады АН, информатика, т. 390, №1, с.27-31, 2003.

  69. B.V. Kryzhanovsky, L.B. Litinskii and A. Fonarev. Parametrical neural network based on the four-wave mixing process. Nuclear Instuments and Methods in Physics Research, A. vol 502, No.2-3, pp. 517 - 519. 2003.

  70. Б.В. Крыжановский, А.Л. Микаэлян. О распознающей способности нейросети на нейронах с параметрическим преобразованием частот. Доклады АН, сер. мат.физика, т. 383, №3, с.318-321, 2002.

  71. A. Fonarev, B.V. Kryzhanovsky. On optimization of neural network recognition capability.Optical Memory&Neural Network, Vol. 11, №1, pp. 11-18 (2002).

  72. B.V. Kryzhanovsky, L.B. Litinskii and A. Fonarev. Optical Neural Network Based on the Parametrical Four-Wave Mixing Process. Proc. of ICONIP-2002. International Conference On Neural Information Processing. Vol.4, pp. 1704-1707, Singapore-2002.

  73. Б.В. Крыжановский, М.В. Крыжановский, А.Л. Микаэлян. Динамическая нейросеть на параметрических осцилляторах с кубической нелинейностью. Труды VIII Всероссийской научно-технической конференции "Нейрокомпьютеры и их применение" НКП-2002. с.985-994. Москва, 21-22 марта 2002.

  74. Крыжановский Б.В., Литинский Л.Б. О векторной модели параметрической нейросети. Искуственный интеллект, №4, с.710-718, 2002.

  75. Б.В. Крыжановский, Л.Б. Литинский. Векторные модели ассоциативной памяти. V Всероссийская научно-техническая конференция "НЕЙРОИНФОРМАТИКА-2003". Лекции по нейроинформатике, т.1, с.71-85.

  76. V.N. Koshelev, B.V. Kryzhanovsky. On Recognation Capability of Hopfield Networks. Pattern Recognition and Image Analysis, Vol.11, №1, pp.47-49 (2001).

  77. Б.В. Крыжановский, В.Н. Кошелев, A. Fonarev. Оценка эффективности рандомизированной памяти Хопфилда. Проблемы передачи информации, том.37, вып.2, с.77-87, 2001.

  78. B.V. Kryzhanovsky, M.V. Kryzhanovsky, V.N. Koshelev and A. Fonarev. Adaptation of Hopfield associative memory parameters in statistic training. Optical Memory&Neural Network, Vol. 10, №2, pp.91-98 (2001).

  79. B.V. Kryzhanovsky, V.M. Kryzhanovsky, A.L. Mikaelian and A. Fonarev. Parametric dynamic neural network recognition power. Optical Memory&Neural Network, Vol. 10, №4, pp.211-218 (2001).

  80. B.V. Kryzhanovsky, V.N. Koshelev, A.L. Mikaelian and A. Fonarev. Recognation Ability of Randomized Hopfield Networks. Optical Memory&Neural Network, Vol.9, №4, 267-276 (2000).
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