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Supervised learning of perceptron and output feedback dynamic networks: a feedback analysis via the small gain theorem

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Supervised learning of perceptron and output feedback dynamic networks: a feedback analysis via the small gain theorem

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Visual crowding illustrates the inadequacy of local vs. global and feedforward vs. feedback distinctions in modeling visual perception

Learning Robot Gait Stability using Neural Networks as Sensory Feedback Function for Central Pattern Generators

Learning Robot Gait Stability using Neural Networks as Sensory Feedback Function for Central Pattern Generators

Multi-Level Error-Resilient Neural Networks

Fast and flexible Kullback-Leibler divergence based acoustic modeling for non-native speech recognition

Different types of feedback change decision criterion and sensitivity differently in perceptual learning

Information Processing and Structure of Dynamical Networks

Fast and flexible Kullback-Leibler divergence based acoustic modeling for non-native speech recognition

Control of a separated boundary layer: reduced-order modeling using global modes revisited

Positive feedbacks contribute to the robustness of the cell cycle with respect to molecular noise

Learning Robot Gait Stability using Neural Networks as Sensory Feedback Function for Central Pattern Generators

Visual crowding illustrates the inadequacy of local vs. global and feedforward vs. feedback distinctions in modeling visual perception

Multi-Level Error-Resilient Neural Networks

Information Processing and Structure of Dynamical Networks

Different types of feedback change decision criterion and sensitivity differently in perceptual learning

Fast and flexible Kullback-Leibler divergence based acoustic modeling for non-native speech recognition

Learning Robot Gait Stability using Neural Networks as Sensory Feedback Function for Central Pattern Generators

Fast and flexible Kullback-Leibler divergence based acoustic modeling for non-native speech recognition

Control of a separated boundary layer: reduced-order modeling using global modes revisited

Positive feedbacks contribute to the robustness of the cell cycle with respect to molecular noise