diff --git a/README.md b/README.md
index 883063c..dfb5081 100644
--- a/README.md
+++ b/README.md
@@ -3,6 +3,8 @@
 Created by:      魏遇卿
 
 Created on:     2023.3
+
+github: [This-weiyuqing/ECG_by_Diffenert_CNN_Test]( https://github.com/This-weiyuqing/ECG_by_Diffenert_CNN_Test)
 # 1 毕业设计的内容和意义
 ## **1.1    毕业设计的内容**
 
@@ -195,6 +197,10 @@ ECG实质上是一种微弱的生物电信号，也因此，其对于噪声的
 
 ##  6.3 网络结构的构建
 
-本部分不做展开描述。您有想法可发邮件至this_weiyuqing@foxmail.com探讨。
+本部分不做展开描述。您有想法可发邮件至如下邮箱探讨。
+        
+    this_weiyuqing@foxmail.com 
 
-# 7 代码运行说明
\ No newline at end of file
+#   7   其他
+
+其他文件请查看毕业论文。
\ No newline at end of file
diff --git a/some-test/test_coplit.py b/some-test/test_coplit.py
new file mode 100644
index 0000000..c8862dd
--- /dev/null
+++ b/some-test/test_coplit.py
@@ -0,0 +1,27 @@
+def get_MAX():
+    MAX = 0
+    for i in range(0, len(X_train)):
+        if MAX < len(X_train[i]):
+            MAX = len(X_train[i])
+    for i in range(0, len(X_test)):
+        if MAX < len(X_test[i]):
+            MAX = len(X_test[i])
+    return MAX
+def made_CNN():
+    # 1D CNN neural network
+    model = Sequential()
+    model.add(Conv1D(32, 5, activation='relu', input_shape=(MAX, 1)))
+    model.add(MaxPooling1D(2))
+    model.add(Conv1D(64, 5, activation='relu'))
+    model.add(MaxPooling1D(2))
+    model.add(Conv1D(128, 5, activation='relu'))
+    model.add(MaxPooling1D(2))
+    model.add(Conv1D(256, 5, activation='relu'))
+    model.add(MaxPooling1D(2))
+    model.add(Conv1D(512, 5, activation='relu'))
+    model.add(MaxPooling1D(2))
+    model.add(Flatten())
+    model.add(Dense(512, activation='relu'))
+    model.add(Dense(5, activation='softmax'))
+    model.summary()
+    return model
\ No newline at end of file