synaptic connection strength concept

src/learn.jl

@@ -65,7 +65,7 @@ function learn!(kfn::kfn_1, correctAnswer::AbstractVector)
     outs = [n.z_t1 for n in kfn.outputNeuronsArray]
     for (i, out) in enumerate(outs)
         if out != correctAnswer[i]   # need to adjust weight
-            kfnError = (kfn.outputNeuronsArray[i].v_th - kfn.outputNeuronsArray[i].v_t) * 
+            kfnError = (kfn.outputNeuronsArray[i].v_th - kfn.outputNeuronsArray[i].v_t1) * 
                         100 / kfn.outputNeuronsArray[i].v_th
 
             # Threads.@threads for n in kfn.neuronsArray
@@ -87,15 +87,9 @@ 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
 
-            # Threads.@threads for n in kfn.neuronsArray
-                for n in kfn.neuronsArray
-                    #WORKING synapticConnStrength
-                    
-
-
-                    #TODO neuroplasticity
-                end
-            
+            synapticConnStrength!(n)
+            #TODO neuroplasticity
+            println("")
         end
 
         for n in kfn.outputNeuronsArray   # merge wRecChange into wRec
@@ -105,7 +99,7 @@ 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
 
-            #TODO synapticConnStrength
+            synapticConnStrength!(n)
             #TODO neuroplasticity
         end