diff --git a/config.json b/config.json
index f436ca6..b7824f4 100644
--- a/config.json
+++ b/config.json
@@ -1,14 +1,14 @@
 {
   "model": {
-    "new": false,
-    "parameters": [10, 10, 5],
-    "path": "C:/HEPL/RNA2/ANN-framework/src/main/resources/snapshots/snapshot-low-learning.json"
+    "new": true,
+    "parameters": [1, 2, 3, 4],
+    "path": "C:/Users/Laurent/Desktop/ANN-framework/src/main/resources/snapshots/snapshot-test.json"
   },
   "training" : {
-    "learning_rate" : 0.003,
-    "max_epoch" : 5000
+    "learning_rate" : 0.01,
+    "max_epoch" : 500
   },
   "dataset" : {
-    "path" : "C:/HEPL/RNA2/ANN-framework/src/main/resources/assets/LangageDesSignes/data_formatted_Low_learning.csv"
+    "path" : "C:/Users/Laurent/Desktop/ANN-framework/src/main/resources/assets/table_3_5.csv"
   }
 }
\ No newline at end of file
diff --git a/src/main/java/com/naaturel/ANN/implementation/multiLayers/ErrorSignalStep.java b/src/main/java/com/naaturel/ANN/implementation/multiLayers/ErrorSignalStep.java
index d36bf2b..c8f83e8 100644
--- a/src/main/java/com/naaturel/ANN/implementation/multiLayers/ErrorSignalStep.java
+++ b/src/main/java/com/naaturel/ANN/implementation/multiLayers/ErrorSignalStep.java
@@ -13,17 +13,27 @@ public class ErrorSignalStep implements AlgorithmStep {
     @Override
     public void run() {
 
-        context.model.forEachNeuron(n -> {
-            if (context.errorSignalsComputed[n.getId()]) return;
+        boolean[] isTotallyComputed = new boolean[1];
 
-            int neuronIndex = context.model.indexInLayerOf(n);
-            float[] signalSum = {0f};
-            context.model.forEachNeuronConnectedTo(n, connected -> {
-                signalSum[0] += context.errorSignals[connected.getId()] * connected.getWeight(neuronIndex);
+        do{
+            isTotallyComputed[0] = true;
+            context.model.forEachNeuron(n -> {
+                if (context.errorSignalsComputed[n.getId()]) return;
+
+                int neuronIndex = context.model.indexInLayerOf(n);
+                float[] signalSum = {0f};
+                boolean[] canBeComputed = {true};
+                context.model.forEachNeuronConnectedTo(n, connected -> {
+                    signalSum[0] += context.errorSignals[connected.getId()] * connected.getWeight(neuronIndex);
+                    canBeComputed[0] &= context.errorSignalsComputed[connected.getId()];
+                });
+
+                if(canBeComputed[0]) {
+                    context.errorSignals[n.getId()] = n.getActivationFunction().derivative(n.getOutput()) * signalSum[0];
+                    context.errorSignalsComputed[n.getId()] = true;
+                }
+                isTotallyComputed[0] &= canBeComputed[0];
             });
-
-            context.errorSignals[n.getId()] = n.getActivationFunction().derivative(n.getOutput()) * signalSum[0];
-            context.errorSignalsComputed[n.getId()] = true;
-        });
+        } while(!isTotallyComputed[0]);
     }
 }
\ No newline at end of file
diff --git a/src/main/java/com/naaturel/ANN/implementation/training/GradientDescentTraining.java b/src/main/java/com/naaturel/ANN/implementation/training/GradientDescentTraining.java
index d7af095..9842746 100644
--- a/src/main/java/com/naaturel/ANN/implementation/training/GradientDescentTraining.java
+++ b/src/main/java/com/naaturel/ANN/implementation/training/GradientDescentTraining.java
@@ -33,7 +33,8 @@ public class GradientDescentTraining implements Trainer {
                 new SimplePredictionStep(context),
                 new SimpleDeltaStep(context),
                 new SquareLossStep(context),
-                new GradientDescentErrorStrategy(context)
+                new GradientDescentErrorStrategy(context),
+                new GradientDescentCorrectionStrategy(context)
         );
 
         new TrainingPipeline(steps)
@@ -48,7 +49,6 @@ public class GradientDescentTraining implements Trainer {
             })
             .afterEpoch(ctx -> {
                 context.globalLoss /= context.dataset.size();
-                new GradientDescentCorrectionStrategy(context).run();
             })
             .withVerbose(true, 5)
             .withTimeMeasurement(true)