Name
Abstract | ||
|---|---|---|
The biologically discovered intrinsic plasticity (IP) learning rule, which changes the intrinsic excitability of an individual neuron by adaptively turning the firing threshold, has been shown to be crucial for efficient information processing. However, this learning rule needs extra time for updating operations at each step, causing extra energy consumption and reducing the computational efficien... |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1109/TNNLS.2021.3084955 | IEEE Transactions on Neural Networks and Learning Systems |
Keywords | DocType | Volume |
IP networks,Neurons,Biological neural networks,Computational modeling,Biological system modeling,Encoding,Biomembranes | Journal | 33 |
Issue | ISSN | Citations |
5 | 2162-237X | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Anguo Zhang | 1 | 5 | 4.17 |
| Xiumin Li | 2 | 0 | 2.03 |
| Yue-Ming Gao | 3 | 18 | 8.88 |
| Yuzhen Niu | 4 | 0 | 0.34 |