refractoring

src/Ironpen.jl

@@ -34,6 +34,7 @@ using .interface
 
 """ 
     Todo:
+        [*1] wRec should not normalized whole. it should be local 5 conn normalized.
         [3] verify that model can complete learning cycle with no error
         [2] neuroplasticity() i.e. change connection
         [] using RL to control learning signal

src/forward.jl

@@ -28,7 +28,7 @@ end
 
 function (kfn::kfn_1)(m::model, input_data::AbstractVector)
     kfn.timeStep = m.timeStep
-    kfn.softreset = m.softreset
+
     kfn.learningStage = m.learningStage
 
     # generate noise

src/learn.jl

@@ -126,7 +126,7 @@ end
 function learn!(n::lif_neuron, error::Number)
     n.eRec = n.phi * n.epsilonRec
  
-    ΔwRecChange = n.eta * error
+    ΔwRecChange = n.eta * error * n.eRec
     n.wRecChange = (n.subExInType * n.wRecChange) + ΔwRecChange
     reset_epsilonRec!(n)
 end
@@ -138,7 +138,7 @@ function learn!(n::alif_neuron, error::Number)
     n.eRec_a = -n.phi * n.beta * n.epsilonRecA
     n.eRec = n.eRec_v + n.eRec_a
 
-    ΔwRecChange = n.eta * error
+    ΔwRecChange = n.eta * error * n.eRec
     n.wRecChange = (n.subExInType * n.wRecChange) + ΔwRecChange
     reset_epsilonRec!(n)
     reset_epsilonRecA!(n)
@@ -149,7 +149,7 @@ end
 function learn!(n::linear_neuron, error::Number)
     n.eRec = n.phi * n.epsilonRec
  
-    ΔwRecChange = n.eta * error
+    ΔwRecChange = n.eta * error * n.eRec
     n.wRecChange = (n.subExInType * n.wRecChange) + ΔwRecChange
     reset_epsilonRec!(n)
 end

src/types.jl

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