| dc.contributor.author | Golovko, Vladimir | |
| dc.contributor.author | Savitsky, Yury | |
| dc.coverage.spatial | Minsk | ru_RU |
| dc.date.accessioned | 2023-11-17T06:38:33Z | |
| dc.date.available | 2023-11-17T06:38:33Z | |
| dc.date.issued | 2003 | |
| dc.identifier.citation | Golovko, V. Computing of Lyapunov Exponents Techniques Using Neural Networks / Vladimir Golovko, Yury Savitsky // The 3nd International Conference on Neural Networks and Artificial Intelligence = Нейронные сети и искусственный интеллект : proceedings, Minsk, November 12–14, 2003 / Belarusian State University of Informatics and Radioelectronicsb ; ed.: Rauf Kh. Sadykhov [et al.]. – Minsk, 2003. – P. 227–231 : il. – Bibliogr.: p. 231 (8 titles). | ru_RU |
| dc.identifier.uri | https://rep.bstu.by/handle/data/37121 | |
| dc.description | Головко Владимир Адамович, Савицкий Юрий Викторович. Методы вычисления показателей Ляпунова с использованием нейронных сетей | ru_RU |
| dc.description.abstract | The authors examine neural network techniques for computing of Lyapunov spectrum using observations from unknown dynamical system. Such an approach is based on applying of multilayer perceptron (MLP) for forecasting the next state of dynamical system from the previous one. It allows for evaluating the Lyapunov spectrum of unknown dynamical system accurately and efficiently only by using scalar time series. The results of experiments are discussed. | ru_RU |
| dc.language.iso | en | ru_RU |
| dc.publisher | BSUIR | ru_RU |
| dc.subject | спектр Ляпунова | ru_RU |
| dc.subject | Lyapunov spectrum | ru_RU |
| dc.subject | многослойная нейронная Сеть | ru_RU |
| dc.subject | multilayer neural networks | ru_RU |
| dc.subject | хаотический процесс | ru_RU |
| dc.subject | chaotic processes | ru_RU |
| dc.subject | dynamical system | ru_RU |
| dc.subject | динамическая система | ru_RU |
| dc.title | Computing of Lyapunov Exponents Techniques Using Neural Networks | ru_RU |
| dc.title.alternative | Методы вычисления показателей Ляпунова с использованием нейронных сетей | ru_RU |
| dc.type | Научный доклад (Working Paper) | ru_RU |
