Hans-Georg Zimmermann

发表

Symbolic Prosody Modeling by Causal Retro-causal NNs with Variable Context Length

Achim F. Müller, Hans-Georg Zimmermann, 2001, ICANN.

A Technical Trading Indicator Based on Dynamical Consistent Neural Networks

Lorenzo Bertolini, Hans-Georg Zimmermann, Ralph Grothmann, 2006, ICANN.

Forecasting with Recurrent Neural Networks: 12 Tricks

Hans-Georg Zimmermann, Ralph Grothmann, Christoph Tietz, 2012, Neural Networks: Tricks of the Trade.

Multi-agent modeling of multiple FX-markets by neural networks

Ralph Neuneier, Hans-Georg Zimmermann, Ralph Grothmann, 2001, IEEE Trans. Neural Networks.

Undershooting: modeling dynamical systems by time grid refinements

Ralph Neuneier, Hans-Georg Zimmermann, Ralph Grothmann, 2002, ESANN.

Learning long-term dependencies with recurrent neural networks

Steffen Udluft, Hans-Georg Zimmermann, Anton Maximilian Schäfer, 2008, Neurocomputing.

Active Portfolio-Management based on Error Correction Neural Networks

Ralph Neuneier, Hans-Georg Zimmermann, Ralph Grothmann, 2001, NIPS.

Forecasting Market Prices with Causal-Retro-Causal Neural Networks

Hans-Georg Zimmermann, Ralph Grothmann, Christoph Tietz, 2011, OR.

A method for computer-aided learning of a recurrent neural network

Hans-Georg Zimmermann, Ralph Grothmann, Christoph Tietz, 2008 .

Segmental duration control with asymmetric causal retro-causal neural networks

Hans-Georg Zimmermann, Çaglayan Erdem, 2001, SSW.

The Recurrent Control Neural Network

Steffen Udluft, Hans-Georg Zimmermann, Anton Maximilian Schäfer, 2007, ESANN.

A New View on Economics with Recurrent Neural Networks

Hans-Georg Zimmermann, Ralph Grothmann, Christoph Tietz, 2016 .

A multi-lingual system for the determination of phonetic word stress using soft feature selection by neural networks

Horst-Udo Hain, Hans-Georg Zimmermann, 2001, SSW.

Recurrent Neural Networks are Universal approximators

Hans-Georg Zimmermann, Anton Maximilian Schäfer, 2007, Int. J. Neural Syst..

Historical Consistent Complex Valued Recurrent Neural Network

Alexey Minin, Hans-Georg Zimmermann, Victoria Kusherbaeva, 2011, ICANN.

Multi-agent FX-Market Modeling Based on Cognitive Systems

Ralph Neuneier, Hans-Georg Zimmermann, Ralph Grothmann, 2001, ICANN.

Complex Valued Artificial Recurrent Neural Network as a Novel Approach to Model the Perceptual Binding Problem

Alois Knoll, Alexey Minin, Hans-Georg Zimmermann, 2012, ESANN.

Modeling Dynamical Systems by Error Correction Neural Networks

Ralph Neuneier, Hans-Georg Zimmermann, Ralph Grothmann, 2002 .

Modeling of the German Yield Curve by Error Correction Neural Networks

Ralph Neuneier, Hans-Georg Zimmermann, Ralph Grothmann, 2000, IDEAL.

Causality Versus Predictability In Neural Network Modeling

Hans-Georg Zimmermann, H. Zimmermann, 2015 .

Comparison of the Complex Valued and Real Valued Neural Networks Trained with Gradient Descent and Random Search Algorithms

Alexey Minin, Hans-Georg Zimmermann, Victoria Kusherbaeva, 2011, ESANN.

Yield curve forecasting by error correction neural networks and partial learning

Hans-Georg Zimmermann, Ralph Grothmann, Christoph Tietz, 2002, ESANN.

Optimal asset allocation for a large number of investment opportunities

Hans-Georg Zimmermann, Ralph Grothmann, 2005, Intell. Syst. Account. Finance Manag..

Recurrent Neural Networks Are Universal Approximators

Hans-Georg Zimmermann, Anton Maximilian Schäfer, H. Zimmermann, 2006, ICANN.

Unsupervised Mutual Information Criterion for Elimination of Overtraining in Supervised Multilayer Networks

Gustavo Deco, William Finnoff, Hans-Georg Zimmermann, 1995, Neural Computation.

How to Train Neural Networks

Ralph Neuneier, Hans-Georg Zimmermann, 2012, Neural Networks: Tricks of the Trade.

Early Brain Damage

Volker Tresp, Ralph Neuneier, Hans-Georg Zimmermann, 1996, NIPS.

computing elements interconnected arrangement and method for computer-aided determination of a second state of a system in a first state space from a first state of the system in the first state space

Hans-Georg Zimmermann, Ralf Neuneier, 2001 .

The Observer-Observation Dilemma in Neuro-Forecasting

Ralph Neuneier, Hans-Georg Zimmermann, 1997, NIPS.

Learning Long Term Dependencies with Recurrent Neural Networks

Steffen Udluft, Hans-Georg Zimmermann, Anton Maximilian Schäfer, 2006, ICANN.

How to Train Neural Networks

Ralph Neuneier, Hans-Georg Zimmermann, R. Neuneier, 1996, Neural Networks: Tricks of the Trade.

Neuro-Fuzzy Methoden in der Finanzanalyse

Ralph Neuneier, Hans-Georg Zimmermann, 1996, Künstliche Intell..

A data-driven method for input feature selection within neural prosody generation

Hans-Georg Zimmermann, Çaglayan Erdem, 2002, 2002 IEEE International Conference on Acoustics, Speech, and Signal Processing.

Extended Regularization Methods for Nonconvergent Model Selection

Ferdinand Hergert, William Finnoff, Hans-Georg Zimmermann, 1992, NIPS.

Update-Techniken in der Transientenanalyse von elektrischen Netzwerken

Hans-Georg Zimmermann, 1988, Simulationstechnik.

Complex Valued Recurrent Neural Network: From Architecture to Training

Alois Knoll, Alexey Minin, Hans-Georg Zimmermann, 2012 .

Recurrent Neural Networks for Industrial Procurement Decisions

Thomas A. Runkler, Hans-Georg Zimmermann, Ralph Grothmann, 2012, KI - Künstliche Intelligenz.

Grundlagenforschung und Softwareentwicklung im Siemensprojekt "Neurodemonstrator"

Wolfram Büttner, Bernd Schürmann, Ferdinand Hergert, 1989, Wissensbasierte Systeme.

Modeling of electric power transformer using complex-valued neural networks

Alois Knoll, Alexey Minin, E. Kholodova, 2011 .

Segmental duration control by time delay neural networks with asymmetric causal and retro-causal information flows

Hans-Georg Zimmermann, Çaglayan Erdem, 2002, ESANN.

Optimal asset allocation for a large number of investment opportunities: Research Articles

Hans-Georg Zimmermann, Ralph Grothmann, 2005 .