Article ID Journal Published Year Pages File Type
425759 Future Generation Computer Systems 2006 6 Pages PDF
Abstract

We consider the problem of designing a general additive neural network which possesses prescribed equilibria. The relation between this design problem and a problem of generating a matrix with specified eiegenvalues, which maps a given set of vectors of another given set, is investigated. The obtained inverse eigenvalue problem is then solved using a gradient flow approach. Working with discretisation of systems of differential equations allows to preserve the original dimension of the problem and could give the possibility of constructing adaptive schemes faster than algebraic one.

Related Topics
Physical Sciences and Engineering Computer Science Computational Theory and Mathematics
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