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Nakajima, Kohei [Editor]; Fischer, Ingo [Editor]

Reservoir computing : theory, physical implementations, and applications

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Singapore: Springer, [2021]

Published in: Natural computing series
Medsker, Larry R. [Editor]

Recurrent neural networks : design and applications

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Boca Raton, FL [u.a.]: CRC Press, 2000

Published in: The CRC Press international series on computational intelligence
Kasper, Klaus [Author]

Spracherkennung mit rekurrenten neuronalen Netzwerken

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Aachen: Shaker, 2000

Published in: Berichte aus der Physik
MacIntyre, Yvonne [Author]

Modellgenerierung mit konnektionistischen Systemen

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2000
Rovithakis, George A. [Author]; Christodoulou, Manolis A. [Author]

Adaptive control with recurrent high-order neural networks : theory and industrial applications

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London; Berlin; Heidelberg [u.a.]: Springer, 2000

Published in: Advances in industrial control
Afzal, Muhammad Zeshan [Author] ; Dengel, Andreas [Degree supervisor]; Eichenberger-Liwicki, Marcus [Degree supervisor] Technische Universität Kaiserslautern, Technische Universität Kaiserslautern Fachbereich Maschinenbau und Verfahrenstechnik

Deep learning in space and time for document image processing

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Kaiserslautern: Technische Universität Kaiserslautern, November 2016

Published in: Informatik
Nürnberger, Andreas [Other]

Recurrent neuro-fuzzy systems for the analysis of dynamic systems

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2001
Gandhi, Vaibhav [Author]

Brain-computer interfacing for assistive robotics : electroencephalograms, recurrent quantum neural networks and user-centric graphical interfaces

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Amsterdam; Boston; Heidelberg: Elsevier, Academic Press, [2015]

Published in: Elsevier science & technology books
Kolen, John F. [Other]; Kremer, Stefan C. [Other]

A field guide to dynamical recurrent networks

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... to E-book via IEEE Xplore (Volltext)

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New York: IEEE Press, c2001 ; Online-Ausg., Piscataway, N.J: IEEE, 2010

Published in: IEEE Xplore Digital Library
Schürmann, Felix [Author]

Exploring liquid computing in a hardware adaptation : construction and operation of a neural network experiment

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... to E-book via DOI (Volltext ; freely accessible)

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2005
De Raedt, Luc [Author]; Hammer, Barbara [Author]; Hitzler, Pascal [Author]; Maass, Wolfgang [Author] ; Luc De Raedt and Barbara Hammer and Pascal Hitzler and Wolfgang Maass [Contributor]

08041 Summary – Recurrent Neural Networks - Models, Capacities, and Applications

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Schloss Dagstuhl – Leibniz-Zentrum für Informatik, 2008
Bille, Shreya [Author]

RNN Based Recommendation Engine : A Paradigm Shift towards Deep Learning

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[S.l.]: SSRN, 2023
Alpay, Tayfun [Author]

Periodicity, Surprisal, Attention: Skip Conditions for Recurrent Neural Networks

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... to E-book via German National Library

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Hamburg: Staats- und Universitätsbibliothek Hamburg Carl von Ossietzky, 2021
Reinhart, Felix [Author]

Reservoir computing with output feedback

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Bielefeld: Universitätsbibliothek Bielefeld, Hochschulschriften, 2012
Tanisaro, Pattreeya [Author]; Heidemann, Gunther [Author] ; Pattreeya Tanisaro and Gunther Heidemann [Contributor]

An Empirical Study on Bidirectional Recurrent Neural Networks for Human Motion Recognition

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Schloss Dagstuhl – Leibniz-Zentrum für Informatik, 2018
Rad, Hossein [Author]; Low, Rand Kwong Yew [Author]; Miffre, Joëlle [Author]; Faff, Robert W. [Author]

The Commodity Risk Premium and Neural Networks

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[S.l.]: SSRN, [2023]
De Raedt, Luc [Author]; Hammer, Barbara [Author]; Hitzler, Pascal [Author]; Maass, Wolfgang [Author] ; Luc De Raedt and Barbara Hammer and Pascal Hitzler and Wolfgang Maass [Contributor]

08041 Abstracts Collection – Recurrent Neural Networks - Models, Capacities, and Applications

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Schloss Dagstuhl – Leibniz-Zentrum für Informatik, 2008
Markert, Jens [Author]

Neural associative memories for language understanding and robot control

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2009
Shen, Ze [Author]; Wan, Qing [Author]; Leatham, David J. [Author]

Bitcoin return volatility forecasting: A comparative study between GARCH and RNN

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Basel: MDPI, 2021
Alpay, Tayfun [Author] ; Wermter, Stefan [Contributor]

Periodicity, Surprisal, Attention: Skip Conditions for Recurrent Neural Networks

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Staats- und Universitätsbibliothek Hamburg Carl von Ossietzky, 2021-01-01

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