Learning by optimization in random neural networks

Date

1998-10-28

Author

Atalay, Mehmet Volkan

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The random neural network model proposed by Gelenbe has a number of interesting features in addition to a well established theory. Gelenbe has also developed a learning algorithm for the recurrent random network model using gradient descent of a quadratic error function. We present a quadratic optimization approach for learning in the random neural network, particularly for image texture reconstruction.

URI

https://hdl.handle.net/11511/55589

Conference Name

13th International Symposium on Computer and Information Sciences (ISCIS 98)

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Department of Computer Engineering, Conference / Seminar

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Citation Formats

M. V. Atalay, “Learning by optimization in random neural networks,” Belek Antalya, TURKEY, 1998, vol. 53, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/55589.