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A neuromorphic network for generic multivariate data classification
Michael Schmuker
, Thomas Pfeil
, Martin Paul Nawrot
Department of Computer Science
School of Physics, Engineering & Computer Science
Biocomputation Research Group
Research output
:
Contribution to journal
›
Article
›
peer-review
78
Citations (Scopus)
41
Downloads (Pure)
Overview
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Keyphrases
Neuromorphic Hardware
100%
Neuromorphic System
100%
Data Classification
100%
Multivariate Data
100%
Lateral Inhibition
66%
Spiking Neural Networks
66%
Hardware System
66%
Successful Implementation
33%
Classification Performance
33%
Computational Principles
33%
Biological Time
33%
Nave Bayes Classifier
33%
Olfactory System
33%
Complex Neural Network
33%
Spike Trains
33%
Neuron Population
33%
Population Coding
33%
Winner-take-all Circuit
33%
Time Matching
33%
Insect Nervous System
33%
Network Dynamics
33%
Computational Neuroscience
33%
Neuromorphic Computing
33%
Supervised Learning
33%
Computing Problems
33%
Nervous System
33%
Transfer Function
33%
Output Neurons
33%
Technical Application
33%
Computer Science
Data Classification
100%
Multivariate Data
100%
Computer Hardware
100%
Neural Network
75%
Transfer Function
25%
Successful Implementation
25%
Supervised Learning
25%
Classification Stage
25%
Classification Performance
25%
Network Dynamic
25%
Bayes Classifier
25%
Nave Bayes
25%
Neuroscience
Neural Network
100%
Lateral Inhibition
66%
Receptor
66%
Nervous System
66%
Olfactory System
33%
Neurobiology
33%
Material Science
Silicon
100%
Electronic Circuit
100%
Neuromorphic Computing
100%