Improving the Accuracy of Neural Network Pattern Recognition by Fractional Gradient Descent

Improving the Accuracy of Neural Network Pattern Recognition by Fractional Gradient Descent

In this paper we propose the fractional gradient descent for increasing the training and work of modern neural networks. This optimizer searches the global minimum of the loss function considering the fractional gradient directions achieved by Riemann-Liouville, Caputo, and Grunwald-Letnikov derivat...

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Xehetasun bibliografikoak
Egile Nagusiak:	Abdulkadirov, R. I., Абдулкадиров, Р. И., Lyakhov, P. A., Ляхов, П. А., Baboshina, V. A., Бабошина, В. А., Nagornov, N. N., Нагорнов, Н. Н.
Formatua:	Статья
Hizkuntza:	English
Argitaratua:	Institute of Electrical and Electronics Engineers Inc. 2024
Gaiak:	Caputo Stochastic gradient descent Convolutional neural networks Fractional derivatives of Riemann-Liouville Grunwald-Letnikov Multilayer perceptron Optimization algorithms
Sarrera elektronikoa:	https://dspace.ncfu.ru/handle/123456789/29336
Etiketak:	Etiketa erantsi Etiketarik gabe, Izan zaitez lehena erregistro honi etiketa jartzen!

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