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Configuring Spiking Neural Networks for (2006)
| Content Provider | CiteSeerX |
|---|---|
| Author | Makino, Takaki Feng, Jianfeng |
| Abstract | We have developed a general framework to configure a spiking neuronal network so that it can precisely generate a desired spatio-temporal pattern of spikes. The unit of spiking neuronal networks employed here is a leaky integrate-and-fire model with a connection delay. We have shown that the required network configuration, and its existence, can be characterized by a set of linear inequalities constructed from the given pattern. The stability of the configured spiking neuronal network is discussed, which lead us to applying some routine methods in linear-programming to solve the set of inequalities, and yields the desirable spiking neural network configuration. To demonstrate the application of our approach, numerical examples with randomly generated patterns were explored and included. |
| File Format | |
| Publisher Date | 2006-01-01 |
| Access Restriction | Open |
| Subject Keyword | Neural Network Neuronal Network General Framework Numerical Example Required Network Configuration Neural Network Configuration Routine Method Leaky Integrate-and-fire Model Configured Spiking Neuronal Network Connection Delay Desired Spatio-temporal Pattern Linear Inequality |
| Content Type | Text |
