Complete controllability of discrete-time recurrent neural networks

Thomas Steinberger, Lucas Zinner

Publikation: Working/Discussion PaperWU Working Paper

13 Downloads (Pure)

Abstract

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)

Publikationsreihe

ReiheReport Series SFB "Adaptive Information Systems and Modelling in Economics and Management Science"
Nummer41

WU Working Paper Reihe

  • Report Series SFB \Adaptive Information Systems and Modelling in Economics and Management Science\

Zitat