Two-level hierarchy with sparsely and temporally coded patterns and its possible functional role in information processing

Authors:
Masaki Nomura;Toshio Aoyagi;Masato Okada
Affiliations:
Department of Applied Analysis and Complex Dynamical Systems, Graduate School of Informatics, Kyoto University, Kyoto 606-8501, Japan and CREST, Japan Science and Technology Corporation, Kawaguchi ...;Department of Applied Analysis and Complex Dynamical Systems, Graduate School of Informatics, Kyoto University, Kyoto 606-8501, Japan and CREST, Japan Science and Technology Corporation, Kawaguchi ...;Kawato Dynamic Brain Project, Japan Science and Technology Corporation, 2-2, Hikaridai, Seika-cho, Soraku-gun, Kyoto 619-0288, Japan and Laboratory for Mathematical Neuroscience, RIKEN Brain Scien ...
Venue:
Neural Networks
Year:
2003

Citing 8
Cited 0

A neural cocktail-party processor

Biological Cybernetics
Conversion of temporal correlations between stimuli to spatial correlations between attractors

Neural Computation
Global competition and local cooperation in a network of neural oscillators

Physica D
A hierarchy of macrodynamical equations for associative memory

Neural Networks
Notions of associative memory and sparse coding

Neural Networks - 1996 Special issue: four major hypotheses in neuroscience
Transform-invariant recognition by association in a recurrent network

Neural Computation
Retrieval dynamics in oscillator neural networks

Neural Computation
Texture segmentation using Gaussian-Markov random fields and neural oscillator networks

IEEE Transactions on Neural Networks

Quantified Score

Hi-index	0.00

Visualization

Abstract

In recent years it has been shown that first order recurrent neural networks trained by gradient-descent can learn not only regular but also simple context-free and context-sensitive languages. However, the success rate was generally low and severe instability ...