Spiking neurons can learn to solve information bottleneck problems and extract independent components

Neural Computation

Volumn 21, Issue 4, 2009, Pages 911-959

  Klampfl, Stefan ^a   Legenstein, Robert ^a   Maass, Wolfgang ^a  

^a GRAZ UNIVERSITY OF TECHNOLOGY   (Austria)

Author keywords

[No Author keywords available]

Indexed keywords

ACTION POTENTIAL; ALGORITHM; ANIMAL; ARTICLE; ARTIFICIAL INTELLIGENCE; BIOLOGICAL MODEL; NERVE CELL PLASTICITY; PHYSIOLOGY; PROPRIOCEPTION; SENSORY RECEPTOR; STATISTICS;

ACTION POTENTIALS; ALGORITHMS; ANIMALS; ARTIFICIAL INTELLIGENCE; MODELS, NEUROLOGICAL; NEURONAL PLASTICITY; PROPRIOCEPTION; SENSORY RECEPTOR CELLS; STOCHASTIC PROCESSES;

EID: 65549123223     PISSN: 08997667     EISSN: 1530888X     Source Type: Journal    
DOI: 10.1162/neco.2008.01-07-432     Document Type: Article

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