Resource title

Complete controllability of discrete-time recurrent neural networks

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Resource description

This paper presents a characterization of complete controllability for the class of discrete-time recurrent neural networks. We prove that complete controllability holds if and only if the rank of the control matrix equals the state space dimension. (author's abstract) ; Series: Report Series SFB "Adaptive Information Systems and Modelling in Economics and Management Science"

Resource author

Thomas Steinberger, Lucas Zinner

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Resource language

en

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application/pdf

Resource resource URL

http://epub.wu.ac.at/440/1/document.pdf

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