On stability and solvability (or, when does a neural network solve a problem?)

Minds and Machines 2 (1):71-83 (1992)
  Copy   BIBTEX


The importance of the Stability Problem in neurocomputing is discussed, as well as the need for the study of infinite networks. Stability must be the key ingredient in the solution of a problem by a neural network without external intervention. Infinite discrete networks seem to be the proper objects of study for a theory of neural computability which aims at characterizing problems solvable, in principle, by a neural network. Precise definitions of such problems and their solutions are given. Some consequences are explored, in particular, the neural unsolvability of the Stability Problem for neural networks.



    Upload a copy of this work     Papers currently archived: 91,349

External links

Setup an account with your affiliations in order to access resources via your University's proxy server

Through your library


Added to PP

32 (#485,568)

6 months
5 (#652,053)

Historical graph of downloads
How can I increase my downloads?

Citations of this work

No citations found.

Add more citations

References found in this work

Computable Analysis.Oliver Aberth - 1984 - Journal of Symbolic Logic 49 (3):988-989.

Add more references