synaptic connection strength concept

src/Ironpen.jl

@@ -1,6 +1,6 @@
 module Ironpen
 
-export kfn_1
+export kfn_1, synapticConnStrength!
 
 
 """ Order by dependencies of each file. The 1st included file must not depend on any other
@@ -35,7 +35,6 @@ using .interface
 """ 
     Todo:
         [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
@@ -57,6 +56,7 @@ using .interface
                 (vt*100)/vth as error 
         [DONE] use LinearAlgebra.normalize!(vector, 1) to adjust weight after weight merge 
         [DONE] reset_epsilonRec after ΔwRecChange is calculated
+        [DONE] synaptic connection strength concept. use sigmoid, turn connection offline
 
     Change from version:    v06_36a
         - 

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
-                    
-
-
+            synapticConnStrength!(n)
             #TODO neuroplasticity
-                end
-            
+            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
 

src/snn_utils.jl

@@ -4,13 +4,13 @@ using Flux.Optimise: apply!
 export calculate_α, calculate_ρ, calculate_k, timestep_forward!, init_neuron, no_negative!,
         precision, calculate_w_change!, store_knowledgefn_error!, interneurons_adjustment!, 
         reset_z_t!, resetLearningParams!, reset_learning_history_params!, reset_epsilonRec!,
-        reset_epsilonRecA!,
+        reset_epsilonRecA!, synapticConnStrength!,
         firing_rate_error!, firing_rate_regulator!, update_Bn!, cal_firing_reg!,
         neuroplasticity!, shakeup!, reset_learning_no_wchange!, adjust_internal_learning_rate!,
         gradient_withloss 
 
 using Statistics, Random, LinearAlgebra, Distributions, Zygote, Flux
-
+using GeneralUtils
 using ..types
 
 #------------------------------------------------------------------------------------------------100
@@ -298,22 +298,21 @@ function synapticConnStrength(currentStrength::AbstractFloat, updown::String, bi
     return updatedStrength
 end
 
-function synapticConnStrength(n::compute_neuron)
+function synapticConnStrength!(n::Union{compute_neuron, output_neuron})
     for (i, connStrength) in enumerate(n.synapticStrength)
         #WORKING
         # check whether connStrength increase or decrease based on usage from n.epsilonRec
-
-        # compute synaptic strength for this conn
-
-        # apply conn lowerlimit and upperlimit
-
+        updown = n.epsilonRec[i] == 0.0 ? "down" : "up"
+        updatedConnStrength = synapticConnStrength(connStrength, updown)
+        updatedConnStrength = GeneralUtils.limitvalue(updatedConnStrength, 
+                        n.synapticStrengthLimit.lowerlimit, n.synapticStrengthLimit.upperlimit)
         # at lowerlimit, mark wRec at this position to 0. for new random synaptic conn
-
-
+        if updatedConnStrength == n.synapticStrengthLimit.lowerlimit[1]        
+            n.wRec[i] = 0.0
         end
-
     end
-
+end
+function synapticConnStrength!(n::input_neuron) end
 
 
 

src/types.jl

@@ -3,7 +3,7 @@ module types
 export 
     # struct
     IronpenStruct, model, knowledgeFn, lif_neuron, alif_neuron, linear_neuron,
-    kfn_1, compute_neuron, neuron, output_neuron, passthrough_neuron, 
+    kfn_1, input_neuron, compute_neuron, neuron, output_neuron, passthrough_neuron, 
 
     # function
     instantiate_custom_types, init_neuron, populate_neuron,