refractoring
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@@ -36,8 +36,6 @@ Base.@kwdef mutable struct model <: Ironpen
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reset epsilon_j.
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"reflect" = neuron will merge wRecChange into wRec then reset wRecChange. """
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learningStage::String = "inference"
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softreset::Bool = false
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timeStep::Number = 0.0
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end
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""" Model outer constructor
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@@ -106,7 +104,6 @@ Base.@kwdef mutable struct kfn_1 <: knowledgeFn
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learningStage::String = "inference"
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error::Union{Float64,Nothing} = nothing
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softreset::Bool = false
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firedNeurons::Array{Int64} = Vector{Int64}() # store unique id of firing neurons to be used when random neuron connection
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firedNeurons_t0::Union{Vector{Bool},Nothing} = nothing # store firing state of all neurons at t0
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@@ -314,7 +311,7 @@ Base.@kwdef mutable struct lif_neuron <: compute_neuron
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timeStep::Number = 0.0 # current time
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wRec::Union{Array{Float64},Nothing} = nothing # synaptic weight (for receiving signal from other neuron)
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v_t::Float64 = rand() # vᵗ, postsynaptic neuron membrane potential of previous timestep
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v_t1::Float64 = 0.0 # vᵗ⁺¹, postsynaptic neuron membrane potential at current timestep
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v_t1::Float64 = rand() # vᵗ⁺¹, postsynaptic neuron membrane potential at current timestep
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v_t_default::Union{Float64,Nothing} = 0.0 # default membrane potential voltage
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v_th::Float64 = 1.0 # vᵗʰ, neuron firing threshold
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vRest::Float64 = 0.0 # resting potential after neuron fired
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@@ -407,7 +404,7 @@ Base.@kwdef mutable struct alif_neuron <: compute_neuron
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timeStep::Union{Number,Nothing} = nothing # current time
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wRec::Union{Array{Float64},Nothing} = nothing # synaptic weight (for receiving signal from other neuron)
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v_t::Float64 = rand() # vᵗ, postsynaptic neuron membrane potential of previous timestep
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v_t1::Float64 = 0.0 # vᵗ⁺¹, postsynaptic neuron membrane potential at current timestep
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v_t1::Float64 = rand() # vᵗ⁺¹, postsynaptic neuron membrane potential at current timestep
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v_t_default::Union{Float64,Nothing} = 0.0
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v_th::Float64 = 1.0 # vᵗʰ, neuron firing threshold
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vRest::Float64 = 0.0 # resting potential after neuron fired
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@@ -515,7 +512,7 @@ Base.@kwdef mutable struct linear_neuron <: output_neuron
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subExInType::Array{Int64} = Vector{Int64}() # store ExIn type of subscribed neurons
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wRec::Union{Array{Float64},Nothing} = nothing # synaptic weight (for receiving signal from other neuron)
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v_t::Float64 = 0.0 # vᵗ, postsynaptic neuron membrane potential of previous timestep
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v_t1::Float64 = 0.0 # vᵗ⁺¹, postsynaptic neuron membrane potential at current timestep
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v_t1::Float64 = rand() # vᵗ⁺¹, postsynaptic neuron membrane potential at current timestep
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v_t_default::Union{Float64,Nothing} = 0.0 # default membrane potential voltage
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v_th::Float64 = 1.0 # vᵗʰ, neuron firing threshold
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vRest::Float64 = 0.0 # resting potential after neuron fired
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