Xing et al., 2022 - Google Patents
Frequency synchronization and excitabilities of two coupled heterogeneous Morris-Lecar neuronsXing et al., 2022
View PDF- Document ID
- 11177899030307629483
- Author
- Xing M
- Song X
- Wang H
- Yang Z
- Chen Y
- Publication year
- Publication venue
- Chaos, Solitons & Fractals
External Links
Snippet
It is well-known that neurons in the same cortical region still have highly heterogeneous responses. These different intrinsic neuronal features play an important role in the connection and coding of the biological nervous system. In this work, we study the response …
- 210000002569 neurons 0 title abstract description 120
Classifications
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- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computer systems based on biological models
- G06N3/02—Computer systems based on biological models using neural network models
- G06N3/06—Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons
- G06N3/063—Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons using electronic means
- G06N3/0635—Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons using electronic means using analogue means
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- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computer systems based on biological models
- G06N3/02—Computer systems based on biological models using neural network models
- G06N3/04—Architectures, e.g. interconnection topology
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computer systems based on biological models
- G06N3/02—Computer systems based on biological models using neural network models
- G06N3/08—Learning methods
- G06N3/082—Learning methods modifying the architecture, e.g. adding or deleting nodes or connections, pruning
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