| 摘要 |
Certain aspects of the present disclosure provide methods and apparatus for a continuous-time neural network event-based simulation. This model is flexible, has rich behavioral options, can be solved directly, and is low complexity. One example method generally includes determining a first state of a neuron model at or shortly after a first event, wherein the neuron model has a closed-form solution in continuous time; and determining a second state of the neuron model at or shortly after a second event, based on the first state. Dynamics of the first and second states are coupled to the neuron model only at the first and second events, respectively, and are decoupled between the first and second events. |
