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Neural spike sorting under nearly 0-dB signal-to-noise ratio using nonlinear energy operator and artificial neural-network classifier
Kyung Hwan Kim
, Sung June Kim
Division of Medical Engineering
Research output
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Contribution to journal
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Article
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peer-review
192
Citations (Scopus)
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Dive into the research topics of 'Neural spike sorting under nearly 0-dB signal-to-noise ratio using nonlinear energy operator and artificial neural-network classifier'. Together they form a unique fingerprint.
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Agricultural and Biological Sciences
Neural Networks
100%
Classification
50%
Semiconductors
50%
Action Potential
50%
Abdominal Ganglia
50%
Aplysia
50%
Neuroscience
Neural Networks
100%
Spike Sorting
100%
Artificial Neural Network
50%
Action Potential
50%
Computer Science
Classification (Machine Learning)
100%
Energy Operator
66%
Artificial Neural Network
33%
Neural Networks
33%
Correct Classification
33%
Trained Neural Network
33%
Social Sciences
Neural Network
100%
Action Potential
66%
Semiconductors
33%
Psychology
Neural Network
100%
Microelectrode
33%
Training Set
33%
Physics
Amplitudes
66%
Artificial Neural Network
33%
Neural Network
33%
Semiconductor
33%
Medicine and Dentistry
Action Potential
50%
Microelectrode
50%
Abdominal Ganglion
50%