Biblio
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2012.
Stability of backpropagtion-decorrelation efficient O(N) recurrent learning. Proc. European Symposium Artificial Neural Networks. :43–48.
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2005. Maximisation of stability ranges for recurrent neural networks subject to on-line adaptation. Proc. European Symposium Artificial Neural Networks. :369–374.
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1999. Mit KI zu mehr Teilhabe in der Arbeitswelt: Potenziale, Einsatzmöglichkeiten und Herausforderungen. Whitepaper aus der Plattform Lernende Systeme.
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2023. Online reservoir adaptation by intrinsic plasticity for backpropagation-decorrelation and echo state learning. Neural Networks. 20:353–364.
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2007. Local structural stability of recurrent networks with time-varying weights. Neurocomputing. 48:39–51.
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2002. Kollaborative Roboter – universale Werkzeuge in der digitalisierten und vernetzten Arbeitswelt. G. W. Maier, G. Engels, E. Steffen (Hrg.): Handbuch Gestaltung digitaler und vernetzter Arbeitswelten. :323-346.
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2020. Kinesthetic Teaching Using Assisted Gravity Compensation for Model-Free Trajectory Generation in Confined Spaces. Gearing Up and Accelerating Cross-Fertilization between Academic and Industrial Robotics Research in Europe. 94:107–127.
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2013. Trends in Neurocomputing at ESANN 2004. Neurocomputing. 64:1–4.
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2005. Recurrent Learning of Input-Output Stable Behaviour in Function Space: A Case Study with the Roessler Attractor. Proc. Int. Conf. Artificial Neural Networks. :761–766.
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1999. "Können Maschinen Ethisches Verhalten Lernen ?" Bericht zum 1. SYnENZ Zirkel der BWG Kommission für Synergie und Intelligenz (SYnENZ) Jahrbuch der Braunschweigischen Wissenschaftlichen Gesellschaft. :117-120.
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2021. Adaptive scene dependent filters for segmentation and online learning of visual objects. Neurocomputing. 70:1235–1246.
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2007. Neural Dynamics for Task-Oriented Grouping of Communicating Agents. Proc. European Symposium Artificial Neural Networks. :531–536.
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2004. Roboterlernen ohne Grenzen ? Lernende Roboter und ethische Fragen Christiane Woopen, Marc Jannes [Hrsg.] Roboter in der Gesellschaft. Technische Möglichkeiten und menschliche Verantwortung. :15-33.
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2019. Lernen und Sicherheit in Interaktion mit Robotern aus Maschinensicht. Robotik und Gesetzgebung. 2:51–71.
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2013. Memory in Backpropagation-Decorrelation O(N) Efficient Online Recurrent Learning. LNCS. 3697:649–654.
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2005. Local input-output stability of recurrent networks with time-varying weights. Proc. European Symposium Artificial Neural Networks. :281–286.
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2000. SYnENZ 2021: Bericht aus der SYnENZ Kommission. Jahrbuch der Braunschweigischen Wissenschaftlichen Gesellschaft. :154-160.
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2022. Humans and Humanoids - Perspectives on Research in Cognition and Robotics. KI - Künstliche Intelligenz. 4:33–36.
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2008. Backpropagation-Decorrelation: online recurrent learning with O(N) complexity. Proc. Int. Joint Conference Neural Networks. 1:843–848.
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2004. Input-Output Stability of Recurrent Neural Networks with Delays using Circle Criteria. Proc. Int. ICSC/IFAC Symposium on Neural Computation. :519–525.
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1998. Robots in the digitalized workplace. The Wiley Blackwell Handbook of the Psychology of the Internet at Work. :403-422.
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2017. Online stability of backpropagation-decorrelation recurrent learning. Neurocomputing. 69:642–650.
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2006. Robust control in closed loops realised by fast signal transmission of infinite gain neurons. Proc. Int. Conf. Artificial Neural Networks. 1:260–266.
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2019.