diff --git a/src/core/data_buffer.py b/src/core/data_buffer.py
index e7fc6aa..c7adb2c 100644
--- a/src/core/data_buffer.py
+++ b/src/core/data_buffer.py
@@ -42,6 +42,8 @@ class DataBuffer:
         self.buffer_mads = [0.0] * self.line_size
         self.buffer_alarms = [0] * self.line_size
         self.last_alarm_channels = []
+        self.episode_history = [[0.0 for _ in range(self.num_of_thinning_iter)] for _ in range(self.line_size)]
+        self.episode_history_timestamps = [[None for _ in range(self.num_of_thinning_iter)] for _ in range(self.line_size)]
 
         self.freq_tag = '' if freq_tag is None else str(freq_tag)
         suffix = f'_{self.freq_tag}' if self.freq_tag else ''
@@ -96,6 +98,13 @@ class DataBuffer:
         except Exception:
             return str(timestamp)
 
+    @staticmethod
+    def _mean_timestamp(timestamps):
+        filtered = [float(ts) for ts in timestamps if ts is not None]
+        if not filtered:
+            return None
+        return sum(filtered) / len(filtered)
+
     def medians(self):
         """
         Вычислить медиану и MAD по строкам буфера.
@@ -178,15 +187,26 @@ class DataBuffer:
         if len(packet_timestamps) != self.line_size:
             raise ValueError('packet_timestamps length must match number of channels')
 
+        sample_idx = self.current_counter - 1
+        for i in range(self.line_size):
+            self.episode_history[i][sample_idx] = float(data[i])
+            self.episode_history_timestamps[i][sample_idx] = packet_timestamps[i]
+
         if self.current_counter == self.thinning_counter:
             updated_column = self.current_column
             for i in range(self.line_size):
-                self.buffer[i][self.current_column] = data[i]
-                self.buffer_timestamps[i][self.current_column] = packet_timestamps[i]
+                samples = self.episode_history[i][:self.thinning_counter]
+                timestamps = self.episode_history_timestamps[i][:self.thinning_counter]
+                self.buffer[i][self.current_column] = float(sum(samples) / len(samples))
+                self.buffer_timestamps[i][self.current_column] = self._mean_timestamp(timestamps)
             self.current_column = (self.current_column + 1) % self.columns_size
             self.medians()
             if self.check_init():
                 self.log_threshold_update(updated_column)
+            for i in range(self.line_size):
+                for j in range(self.thinning_counter):
+                    self.episode_history[i][j] = 0.0
+                    self.episode_history_timestamps[i][j] = None
             self.current_counter = 1
             if self.current_column == 0:
                 if self.thinning_counter == 1:
@@ -199,6 +219,7 @@ class DataBuffer:
         else:
             self.current_counter += 1
 
+
     def check_alarm(self, data):
         """
         Проверка триггера системы по dBFS во времени.