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The Training of Feed-Forward Neural Networks
| dc.contributor.author | Golovko, V. | ru |
| dc.contributor.author | Dunets, A. | ru |
| dc.contributor.author | Savitsky, Y. | ru |
| dc.coverage.spatial | Brest | ru |
| dc.date.accessioned | 2021-07-27T08:09:33Z | |
| dc.date.available | 2021-07-27T08:09:33Z | |
| dc.date.issued | 1999 | |
| dc.identifier.citation | Golovko, V. The Training of Feed-Forward Neural Networks / V. Golovko, A. Dunets, Y. Savitsky // International Conference on Neural Networks and Artificial Intelligence ICNNAI'99 = Международная конференция по нейронным сетям и искусственному интеллекту ICNNAI'99 : Proceedings, Brest, Belarus, 12–15 October 1999 / Brest Polytechnic Institute, Department of Computers and Laboratory of Artificial Neural Networks, Belarus Special Interest Group of International Neural NetWork Society, International Neural NetWork Society, Belarusian State University of Informatics and Radioelectronics (Belarus), Belarusian Academy of Sciences, Institute of Engineering Cybemetics (Belarus), Universidad Politechnica de Valencia (Spain), Institute of Computer Information Technologies (Ukraine, Ternopil) ; ed. V. Golovko. – Brest : BPI, 1999. – P. 36–39. | ru |
| dc.identifier.uri | https://rep.bstu.by/handle/data/20667 | |
| dc.description.abstract | The training of multilayer perceptron is generally a difficult task. Excessive training times and lack of convergence to an acceptable solution are frequently reported. This paper discribes new training methods of feedforward neural networks. In comparison with standard backpropagation algorithm it has smaller time complexity and better convergence. The testing of the proposed algorithm was carried out on a coding Information task. The results of experiments are discussed. | ru |
| dc.language.iso | en | ru |
| dc.publisher | BPI | ru |
| dc.title | The Training of Feed-Forward Neural Networks | ru |
| dc.type | Научный доклад (Working Paper) | ru |
