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Whenever the membrane potential vx reached the threshold level (Eq. 6), a spike was triggered, vx was set to a reset value c and u was increased of a fixed value d.
u R represents the reset value and u th the threshold value.
Indeed, in our model, the reset value V reset is not a constant.
We assume that they instantaneously relax toward a reset value of the voltage V R ≈ − 60 mV.
Since the reset value is random (see below and Figure 1), this assumption has no impact on the dynamics.
Parameter σ 0 plays the role of a reset value and is chosen smaller than σ on.
Similar(41)
Switch –i toggles initializing the timeframes using the reset values of the latches.
This paper addresses the second question on how to determine the after reset values.
Resetting action has two main characteristics which should be determined: (a) when the controller states are reset and (b) how the after reset values of the controller states are determined.
In order to design a reset law for real time applications, a model predictive strategy is proposed that specifies the after reset values by minimizing a quadratic performance index.
A theta neuron is formally equivalent to a QIF neuron with infinite positive threshold and infinite negative reset values.
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