Artificial Neural Networks and Machine Learning – ICANN 2012 - Lecture Notes in Computer Science
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Published By Springer Berlin Heidelberg

9783642332685, 9783642332692

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Adaptive Neural Oscillator with Synaptic Plasticity Enabling Fast Resonance Tuning

Artificial Neural Networks and Machine Learning – ICANN 2012 - Lecture Notes in Computer Science ◽

10.1007/978-3-642-33269-2_57 ◽

2012 ◽

pp. 451-458 ◽

Cited By ~ 5

Author(s):

Timo Nachstedt ◽

Florentin Wörgötter ◽

Poramate Manoonpong

Keyword(s):

Synaptic Plasticity ◽

Neural Oscillator ◽

Resonance Tuning

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Spectral Signal Unmixing with Interior-Point Nonnegative Matrix Factorization

Artificial Neural Networks and Machine Learning – ICANN 2012 - Lecture Notes in Computer Science ◽

10.1007/978-3-642-33269-2_9 ◽

2012 ◽

pp. 65-72 ◽

Cited By ~ 2

Author(s):

Rafal Zdunek

Keyword(s):

Interior Point ◽

Matrix Factorization ◽

Nonnegative Matrix Factorization ◽

Nonnegative Matrix ◽

Spectral Signal

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Constructing Robust Liquid State Machines to Process Highly Variable Data Streams

Artificial Neural Networks and Machine Learning – ICANN 2012 - Lecture Notes in Computer Science ◽

10.1007/978-3-642-33269-2_76 ◽

2012 ◽

pp. 604-611 ◽

Cited By ~ 12

Author(s):

Stefan Schliebs ◽

Maurizio Fiasché ◽

Nikola Kasabov

Keyword(s):

Data Streams ◽

Liquid State ◽

State Machines ◽

Variable Data

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Reservoir Sizes and Feedback Weights Interact Non-linearly in Echo State Networks

Artificial Neural Networks and Machine Learning – ICANN 2012 - Lecture Notes in Computer Science ◽

10.1007/978-3-642-33269-2_63 ◽

2012 ◽

pp. 499-506 ◽

Cited By ~ 3

Author(s):

Danil Koryakin ◽

Martin V. Butz

Keyword(s):

Echo State Networks

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Making a Reinforcement Learning Agent Believe

Artificial Neural Networks and Machine Learning – ICANN 2012 - Lecture Notes in Computer Science ◽

10.1007/978-3-642-33269-2_55 ◽

2012 ◽

pp. 435-442

Author(s):

Klaus Häming ◽

Gabriele Peters

Keyword(s):

Reinforcement Learning ◽

Learning Agent

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A Dynamic Field Architecture for the Generation of Hierarchically Organized Sequences

Artificial Neural Networks and Machine Learning – ICANN 2012 - Lecture Notes in Computer Science ◽

10.1007/978-3-642-33269-2_4 ◽

2012 ◽

pp. 25-32 ◽

Cited By ~ 7

Author(s):

Boris Durán ◽

Yulia Sandamirskaya ◽

Gregor Schöner

Keyword(s):

Dynamic Field

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Exploratory Behaviour Depends on Multisensory Integration during Spatial Learning

Artificial Neural Networks and Machine Learning – ICANN 2012 - Lecture Notes in Computer Science ◽

10.1007/978-3-642-33269-2_38 ◽

2012 ◽

pp. 296-303 ◽

Cited By ~ 3

Author(s):

Denis Sheynikhovich ◽

Félix Grèzes ◽

Jean-Rémi King ◽

Angelo Arleo

Keyword(s):

Multisensory Integration ◽

Spatial Learning ◽

Exploratory Behaviour

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Learning Representations for Animated Motion Sequence and Implied Motion Recognition

Artificial Neural Networks and Machine Learning – ICANN 2012 - Lecture Notes in Computer Science ◽

10.1007/978-3-642-33269-2_37 ◽

2012 ◽

pp. 288-295 ◽

Cited By ~ 3

Author(s):

Georg Layher ◽

Martin A. Giese ◽

Heiko Neumann

Keyword(s):

Motion Recognition ◽

Implied Motion ◽

Motion Sequence

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How Degrading Networks Can Increase Cognitive Functions

Artificial Neural Networks and Machine Learning – ICANN 2012 - Lecture Notes in Computer Science ◽

10.1007/978-3-642-33269-2_24 ◽

2012 ◽

pp. 185-192 ◽

Cited By ~ 1

Author(s):

Adam Tomkins ◽

Mark Humphries ◽

Christian Beste ◽

Eleni Vasilaki ◽

Kevin Gurney

Keyword(s):

Cognitive Functions

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Cyfield-RISP: Generating Dynamic Instruction Set Processors for Reconfigurable Hardware Using OpenCL

Artificial Neural Networks and Machine Learning – ICANN 2012 - Lecture Notes in Computer Science ◽

10.1007/978-3-642-33269-2_22 ◽

2012 ◽

pp. 169-176

Author(s):

Jörn Hoffmann ◽

Frank Güttler ◽

Karim El-Laithy ◽

Martin Bogdan

Keyword(s):

Reconfigurable Hardware ◽

Instruction Set ◽

Instruction Set Processors

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Artificial Neural Networks and Machine Learning – ICANN 2012 - Lecture Notes in Computer ScienceLatest Publications

TOTAL DOCUMENTS

H-INDEX

Published By Springer Berlin Heidelberg

Adaptive Neural Oscillator with Synaptic Plasticity Enabling Fast Resonance Tuning

Spectral Signal Unmixing with Interior-Point Nonnegative Matrix Factorization

Constructing Robust Liquid State Machines to Process Highly Variable Data Streams

Reservoir Sizes and Feedback Weights Interact Non-linearly in Echo State Networks

Making a Reinforcement Learning Agent Believe

A Dynamic Field Architecture for the Generation of Hierarchically Organized Sequences

Exploratory Behaviour Depends on Multisensory Integration during Spatial Learning

Learning Representations for Animated Motion Sequence and Implied Motion Recognition

How Degrading Networks Can Increase Cognitive Functions

Cyfield-RISP: Generating Dynamic Instruction Set Processors for Reconfigurable Hardware Using OpenCL

Artificial Neural Networks and Machine Learning – ICANN 2012 - Lecture Notes in Computer Science
Latest Publications