Common mistakes in neural network training

Research output: Contribution to journalArticlepeer-review


Although artificial neural networks are not really considered to be similar to biological neural networks, the metaphor is strong enough when we describe the activities such as behaviour or reactions to various inputs. Artificial neural network systems are based on biological neurons. Researchers in the neural network are often failed to have a full understanding of the hypotheses and synthesize. This paper is based on and an extension of author's present and past work to highlight this problem. IF AC.

Original languageEnglish
Pages (from-to)383-385
Number of pages3
JournalIFAC Proceedings Volumes (IFAC-PapersOnline)
Issue number15
Publication statusPublished - 2003
Event5th IFAC Symposium on Modelling and Control in Biomedical Systems 2003 - Melbourne, Australia
Duration: 21 Aug 200323 Aug 2003


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