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docs/modeling/neurons.md

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```
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### The Resonate-and-Fire (RAF) Cell
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This cell models dynamics over voltage `v` and a angular driver state/variable `w`; these
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two variables result in a dampened oscillatory spiking neuronal cell). In effect, the
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resonatoe-and-fire (RAF) model (or "resonator") evolves as a result of two coupled
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differential equations. (Note that this cell supports either Euler or RK-2 integration.)
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```{eval-rst}
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.. autoclass:: ngclearn.components.RAFCell
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.. automethod:: advance_state
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.. automethod:: reset
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```
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### The Izhikevich Cell
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This cell models dynamics over voltage `v` and a recover variable `w` (where `w`

ngclearn/components/__init__.py

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from .neurons.spiking.izhikevichCell import IzhikevichCell
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from .neurons.spiking.RAFCell import RAFCell
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## point to transformer/operater component types
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from .other.varTrace import VarTrace
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from .other.expKernel import ExpKernel
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from .input_encoders.latencyCell import LatencyCell
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from .input_encoders.phasorCell import PhasorCell
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## point to synapse component types
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from .synapses.denseSynapse import DenseSynapse
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from .synapses.staticSynapse import StaticSynapse

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