refractoring

src/Ironpen.jl

@@ -34,9 +34,9 @@ using .interface
 
 """ 
     Todo:
-        [9] verify that model can complete learning cycle with no error
-        [*5] synaptic connection strength concept. use sigmoid, turn connection offline
-        [8] neuroplasticity() i.e. change connection
+        [3] verify that model can complete learning cycle with no error
+        [*1] synaptic connection strength concept. use sigmoid, turn connection offline
+        [2] neuroplasticity() i.e. change connection
         [] using RL to control learning signal
         [] consider using Dates.now() instead of timestamp because time_stamp may overflow
         [] training should include adjusting α, neuron membrane potential decay factor

src/learn.jl

@@ -87,11 +87,15 @@ function learn!(kfn::kfn_1, correctAnswer::AbstractVector)
             LinearAlgebra.normalize!(n.wRec, 1)
             n.wRec .*= nonFlipedSign  # set weight that fliped sign to 0 for random new connection
 
-            #WORKING synapticConnStrength
+            # Threads.@threads for n in kfn.neuronsArray
+                for n in kfn.neuronsArray
+                    #WORKING synapticConnStrength
+                    
+
+
+                    #TODO neuroplasticity
+                end
             
-
-
-            #TODO neuroplasticity
         end
 
         for n in kfn.outputNeuronsArray   # merge wRecChange into wRec

src/snn_utils.jl

@@ -291,9 +291,9 @@ end
 """
 function synapticConnStrength(currentStrength::AbstractFloat, bias::Number=0)
     currentStrength += bias
-    currentStrength - (1.0 - sigmoid(currentStrength))
-    currentStrength -= bias
-    return currentStrength
+    updatedStrength - (1.0 - sigmoid(currentStrength))
+    updatedStrength -= bias
+    return updatedStrength
 end