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State Observability In Recurrent Neural Networks (1993)

Abstract
We obtain a characterization of observability for a class of nonlinear systems which appear in neural networks research. Keywords: Recurrent neural networks, observability. This research was supported in part by US Air Force Grant AFOSR-91-0346, and also by an INDAM (Istituto Nazionale di Alta Matematica Francesco Severi, Italy) fellowship. Rutgers Center for Systems and Control December 1992, rev May 1993 3 Also: Universita' di Padova, Dipartimento di Matematica, Via Belzoni 7, 35100 Padova, Italy. STATE OBSERVABILITY IN RECURRENT NEURAL NETWORKS y Francesca Albertini z Eduardo D. Sontag Department of Mathematics Rutgers University, New Brunswick, NJ 08903 E-mail: albertin@hilbert.rutgers.edu, sontag@hilbert.rutgers.edu Key words: Recurrent neural networks, observability ABSTRACT We obtain a characterization of observability for a class of nonlinear systems which appear in neural networks research. 1 Introduction Systems consisting of a large number of interconnected "neurons...

Publication details
Download http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.52.1694
Source http://www.math.rutgers.edu/~sontag/FTP_DIR/obs-sigma.ps.gz
Publisher IEEE Publications
Contributors CiteSeerX
Repository CiteSeerX - Scientific Literature Digital Library and Search Engine (United States)
Keywords Key words, Recurrent neural networks, observability
Type text
Language English
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