Impact of noise structure and network topology on tracking speed of neural networks

Neural Networks

Volumn 24, Issue 10, 2011, Pages 1110-1119

  Huang, Longwen ^a   Cui, Yuwei ^b   Zhang, Danke ^c,d   Wu, Si ^d  

^a PEKING UNIVERSITY   (China)

^b UNIVERSITY OF SCIENCE AND TECHNOLOGY OF CHINA   (China)

^c SOUTH CHINA UNIVERSITY OF TECHNOLOGY   (China)

^d INSTITUTE OF GEOLOGY AND GEOPHYSICS   (China)

Author keywords

Fast neural computation; Network topology; Noise structure; Tracking speed

Indexed keywords

COMPUTATIONAL TASK; EXTERNAL INPUT; FIRING RATES; HODGKIN-HUXLEY MODELS; IMPACT OF NOISE; LINEAR INTEGRATE-AND-FIRE MODEL; NETWORK DYNAMICS; NETWORK MODELS; NETWORK RESPONSE; NETWORK TOPOLOGY; NEURAL COMPUTATIONS; NEURAL SYSTEMS; NOISE STRUCTURES; PROCESS INFORMATION; STATIONARY STATE; TIME VARYING; TRACKING SPEED; TRANSIENT NETWORK;

ELECTRIC NETWORK TOPOLOGY; TIME VARYING NETWORKS; TOPOLOGY;

NEURAL NETWORKS;

ARTICLE; ARTIFICIAL NEURAL NETWORK; CONTROLLED STUDY; MEMBRANE POTENTIAL; NOISE; PRIORITY JOURNAL; SIMULATION; STATISTICAL MODEL; STIMULUS RESPONSE; SYNAPSE; TASK PERFORMANCE;

ACTION POTENTIALS; ANIMALS; ARTIFACTS; CEREBRAL CORTEX; HUMANS; LINEAR MODELS; MEMBRANE POTENTIALS; MODELS, NEUROLOGICAL; NERVE NET; NEURAL NETWORKS (COMPUTER); NEURONS; REACTION TIME; SYNAPTIC TRANSMISSION;

EID: 80054781536     PISSN: 08936080     EISSN: 18792782     Source Type: Journal    
DOI: 10.1016/j.neunet.2011.05.018     Document Type: Article

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