diff --git a/.obsidian/app.json b/.obsidian/app.json
index c3d850d..d9f71cd 100644
--- a/.obsidian/app.json
+++ b/.obsidian/app.json
@@ -1,3 +1,3 @@
 {
-  "attachmentFolderPath": "./附件"
+  "attachmentFolderPath": "./file_other"
 }
\ No newline at end of file
diff --git a/.obsidian/plugins/pdf-plus/data.json b/.obsidian/plugins/pdf-plus/data.json
index 5d3a021..9c820d4 100644
--- a/.obsidian/plugins/pdf-plus/data.json
+++ b/.obsidian/plugins/pdf-plus/data.json
@@ -263,8 +263,8 @@
   "newFileTemplatePath": "",
   "newPDFLocation": "current",
   "newPDFFolderPath": "",
-  "rectEmbedStaticImage": false,
-  "rectImageFormat": "data-url",
+  "rectEmbedStaticImage": true,
+  "rectImageFormat": "file",
   "rectImageExtension": "webp",
   "zoomToFitRect": false,
   "rectFollowAdaptToTheme": true,
diff --git a/.obsidian/workspace.json b/.obsidian/workspace.json
index e4afa03..1f8a511 100644
--- a/.obsidian/workspace.json
+++ b/.obsidian/workspace.json
@@ -6,7 +6,6 @@
       {
         "id": "9e798c20fcdda0d5",
         "type": "tabs",
-        "dimension": 46.98457223001403,
         "children": [
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@@ -15,10 +14,10 @@
               "type": "pdf",
               "state": {
                 "file": "考研/math/27张宇基础30讲高数.pdf",
-                "page": 11,
-                "left": -20,
-                "top": 688,
-                "zoom": 0.7541107430587508
+                "page": 17,
+                "left": -187,
+                "top": 241,
+                "zoom": 0.7
               },
               "icon": "lucide-file-text",
               "title": "27张宇基础30讲高数"
@@ -27,9 +26,8 @@
         ]
       },
       {
-        "id": "bcd17cd702da37c6",
+        "id": "bfb010d934f3da16",
         "type": "tabs",
-        "dimension": 53.01542776998597,
         "children": [
           {
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@@ -37,12 +35,12 @@
             "state": {
               "type": "markdown",
               "state": {
-                "file": "考研/math/002_第1讲.md",
+                "file": "超级备忘/机器学习/机器视觉.md",
                 "mode": "source",
                 "source": false
               },
               "icon": "lucide-file",
-              "title": "002_第1讲"
+              "title": "机器视觉"
             }
           }
         ]
@@ -102,8 +100,7 @@
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     ],
     "direction": "horizontal",
-    "width": 215.5,
-    "collapsed": true
+    "width": 215.5
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@@ -208,8 +205,12 @@
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-    "考研/math/27张宇基础30讲高数.pdf",
     "考研/math/002_第1讲.md",
+    "考研/math/27张宇基础30讲高数.pdf",
+    "考研/math/file_other/27张宇基础30讲高数.webp",
+    "考研/math/file_other",
+    "考研/math/001_前言.md",
+    "考研/math/003_第2讲.md",
     "考研/math/009_第8讲.md",
     "考研/math/012_第11讲.md",
     "考研/math/014_第13讲.md",
@@ -218,8 +219,6 @@
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     "27张宇基础30讲高数 2.webp",
     "27张宇基础30讲高数 1.webp",
-    "考研/math/003_第2讲.md",
-    "考研/math/001_前言.md",
     "考研/math/002_## 第1讲.md",
     "考研/math/019_第17讲.md",
     "考研/math/017_第15讲.md",
@@ -241,7 +240,6 @@
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     "考研/math/images/ff2dd438eb3d4bec3a1caaf1dfaaa2b98b4e5ec9e763729a8b2525866aa40064.jpg",
     "考研/math/images/ff2cdb08edd1a682a2ef230390725aeee27b501af98d5b27e2f4e0a57e3f2fd2.jpg",
-    "考研/math/images/ff2bf26681da637d5740cdf9a96b0229d2c29427b742e43ce5cf5bf86d9cefd1.jpg",
     "考研/math/images",
     "考研/math/020_## 第18讲.md",
     "考研/math/019_## 第17讲.md",
@@ -251,7 +249,6 @@
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     "未命名 1.base",
-    "超级备忘/激光原理",
-    "超级备忘/图像处理"
+    "超级备忘/激光原理"
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 }
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diff --git a/考研/.DS_Store b/考研/.DS_Store
index 70ab287..4035546 100644
Binary files a/考研/.DS_Store and b/考研/.DS_Store differ
diff --git a/考研/math/002_第1讲.md b/考研/math/002_第1讲.md
index c747fff..3ff18b3 100644
--- a/考研/math/002_第1讲.md
+++ b/考研/math/002_第1讲.md
@@ -1,7 +1,5 @@
+[[27张宇基础30讲高数.pdf#page=10|27张宇基础30讲高数, p.10]]
 ## 第1讲
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do0N1ddtSKVV/4rMHKd1ss9I97H0ziAKeWfudpZ4+qt2ymqqR9+ELhE9bYQs1JFMYaJlA9X4eKo70J4cWvnYsCbyVrcG+exy+aOv7pRfJ7lfP74fP5MVXetO1abLiuVvV9HSosQJbbPAmE3Fc/fgG4m+5U1MB9wmZV5eTfS/tPuDd4hMbadtpay0M3oq6KoYIFObt9ll9t+sEaMGMxEmrtzZGRitmeU1VXWbnfuLjCB+6rZ1rDbsE2ha9IxopDG7vDuLevz8mh39KRwv3+kcqwlnFIKJfACu0dnhPu83gMfX+V5QfgnvgrgYQuPO8mCwUltIJI1E0NGG6qFiUJdkj2ztxOLKV/jkV5FGwzAPqe76BhHT5bRaWEbtSUmGByHOvTCzxvzgHBdacpxgmLWu1/jaWj9Y1wJkMDzp3RbVFDPV94K200kuQwnVDu9ncHp/dhGtr+vmHXWxIDquyexBSe41UBJzFDFcBfL5wBSecUY/Hbj16c6lSjL7Zu8E3wOKoTjoZeNY5XywwrtSuZGZGdUEAjUk9s4R0ZCBOPvHEhpT8pZK47oZE4I/y6UyeBmwEtCMlkw37/XDnpIJIkL5H/aS10lRo3iEj6snKxe3WfSacedImREE+GFIoLTMR/pnp926NLt7jEBTKrAfeAMVxhx6TcYDQHK5V7uYmeSzHN3tLcjoSQdxJxNtPfxG5hbexfiZs4i4pIBX2j3gGdpELZnoJQnRj+b/JtIhLnz6xHYEmBNZ5sMfpD6qvo0TboYADIx68IXdYzjPVRMDb7BbgUfJc/ELSG9mlnfzdyaYhbZYLhisWbDCfX1dnez8ytdODGzro5vc71SYDsQIJZCYay+aLprDhhxLXO1qccoz3p5GsZn3yWBcehBu6MtUrJb2S/Dfmub3BoIiLCg/3M+tC2RoPNefeTOwhs5LqeGZRn1fiG6Q9S/Mr0l8epdN0EC3aKe8H8YzWsMh1l7p+ycbpcovDWwfmelxz8sEDY2hdkMLPoa2aoO4Hf3s1n6ffvn/YlEgCVk5vePZY+fVHOxelVZ7G1QjidNvGqE4YPob/5d6QziD9MRZEjexkXlUMd+eFaj2QgfsPFE76rQvHUFQapBuf8+DYo91BB9hy4XrWp8YSei4KKSVBQJjpr3kTrecYMeqfj0XB4zERquvN/ALFL/1GQY+kCedh2bkBYCTs2wP4XOz9Dk9xYyHsAW02hTLkWUDEs+isW6s5dNccJVr08XPHhVbL8mFvT8s7zJ8pVVgXEMEyAjWaJShi55m2Ut3DN8XZMo8P+kBcFrTJp6vkkr36QbCqIb2Bw9qImBDMFUNcIU6atXI4DK58AdikwOdPrKmR2rCWW/KIYnJLmRMqMshCQtO+u2twu6/vOpL7lB/aCTldCVYcPeom7giZiqOw8QOtN5yA8p3RPEIa1SjKYBkEsl9ud20j5vWaNZ4hjzsleNkZhY1oxKWcWw7mnnqPTZybEt/eUAEVEhNaL57zUk2RAfxKlWVoH3weO2owvH0G7D99+SmajIh6/6wTOk2LaveO4qSfhwQ8pqRmighR8bZpgFDXg1vVlYDyxXy8WVKWdTLn7CvL2xd+7YZh53fbcLITOagKNOoAvm5RtagP0K7sW0gHpID0hWH69EJRrkLKSYqCPFJZq7V/0BTiB7VYd71Z0be+lskjd+fYQIX/PYUWgvJ4X+lC6yoLl6T0EOYNWeWJ8lwIhm4FexJBhoshFWpTTH3S/7fORLssfxSsBp4NvV7Cn/XwKKOwFd8UO/zfvf8tprzwuVqlZu1u9NO6VY42jJ+Icr6tGtFOQIz6wUEZM8g3S14FAA56LaP3330FbsVSuMbaYhII95EKI8h2vRUeTZU29sERKTkkBQBiITAlk+5rqNmBGdxo/d5tz51pkwXdEendE8c9wAkg5j6I+9U1xNOX6UiWAAxOeLW5E5CRJDb3x/R636UKs30hTOSEZ2PRGBXQ9vQ5fyF0GdVBP2AWy8mRw530tjzm5Wyo0mU2nsj/52VAlpjr9B+b6XVLyVhRiAW5/v5SgB+IWhSwf2kGpna7d2rJRqyqY5p5DpvyjJ7YOLRvK1z2GizrjP8wFOgpnOtIaSeecu0y6IqtfyOlVnBUo2s7wigjL7srkSlk2uIGgpxrIxpbxnJBIdA/aLwZxo65kKLB4ZjwnXLwQqpJnzjiChncQYO4MqrWi1OGo5W9aUWE8qfYON5ue4dGJ55WZoW5gD1H+XLC7ifzFVDdWJwrh73rwSApnVkg003pSmpRCW9NL5fvBbK8op0Hf9sILCIi/9J1IcfKCTp1kYDHjbX0ik7Wtmx6r1CbnWTDMaWFwHV973gLcJqTOnw7fQDYNOnJgBoajyj60Eiptg3rBr2VrLdENFcfAbxUdZnCnTdrKc6Af/O3a+y/2bp++jwgpl/QvpDVjxoOY9Y3LYS+69XqMIgOq/aZaNrdAxv89XZQTJfleE0+g073oILNJz9ZluPoaAvXMkYKaUQX57prJSzRIuAw104b4VjKaEqdebhLM9EQxVsgIw9OEdHuEitkoMGSMkaKppKAQ1Ff9v67Pa9EW+fR+xxz1aoyj8286CuejKpZejQqiiX2Q6HuES0Hvdf5Osztd3SAVUv0l3kqGrv++akauZeJnSFDk9ALqXXtpe9xVkN+VJTGULueAYY4hYSAJzVNe9OOOuyq6D+BAWCgaLpMyYYi44CFeK8+0049ifCEQS6wPrhe7u1Ee/bgJyctYHCXLCCJzApg7qzrvxjRBaiJJpg7HucqVil3D4KLhxQneRFtyW0PS8hceIVSh5pQvQgwiHyvqXoUOZJtjz5XWuwWtwUgt6n27Uz7IpekwMwYULvumgvy1mjhCFDosN4lCZo7TnFzaeKDVSQaLoAQ8YLwYxZyx0Dfv6viVfsDS5mUqEstLYYM3upPyvz1IDY6OjDtjikA0PeHx1hWK9WEdaaNtEhgW3oOlDk9hr/Iq7l23sxGUNxV9BBsymUmC9R8tMEkrJ/OV/Oi148u0lcCFNz6VPuClc8ipJTRZaBflXJIwp8fc+k8ujJrLQuYVS3zcCMnJH9M7h3lmq5DATuC0E1h+8Fz0JEOtWTziWh/71kYbb9hIiU0VhX1EoYH9lII4AV77wgAiN/yWDRP4DQJUfgHUcOqLtOhlU4tPbg3PCDv0Lgxy0aWMScIAXd0v3TWLFCJJttP2rl/eenTkHRoIsVOmWN4GhX2X28lgWGk74ByQxEXQPchNX12w+p52xO760rzGIBsXvlzYFMNO01BLVjxs2jV7AkV3RTxjvLDwHcTLGR2pmtCbHhxOrD+tnGhJw3UEmJFYQnT8nY2ij0ATAW+gQlNDi3+yDj/PPe0ct37XFdwpCtiFdfBJYUkqFk3Vmab+2NgilUk4ak8/5pKq08mclAzP7Uee4O4A8jSwHUWhO5COR2742gwkI1Mrhla7i7ZMC739EyNSVmmz6rg41FrhdxnjV/NNvCC1QZKwrEhJOalL79vdMon4fWhY7kP+ryaE6y8webBB6e9UsSpfKiVdvQ3VNl+OnYJKzRf7EqJbQ2JmHHV5Ctorl4Dyp4oWmevynLtj7ENKUa9ITc8CRnsAE2ShA5clizs+jms3tWTtbzOURyMKFOUYnerV37X5IFiku0RdhefPMYlwe6mLlJyBoGgs2yRx9r0pKYrA2gDg3g8drWhpqXaeIja0wsbjnmMaRzuAUVX6aMRsrAZryX/5/tdw/Gjb21aQL0/NC+monZatqsEqF0QqOIh/1d9ImcrkDLxeo0ssGxh2Lm3Q8NQfybWHouh74beRBS8DAekBF+Us6YrnaM/bc9x7IbPE5u8LBgqQPRVJfORk08IY8KX4tbxBtPjqYs2kfNy8Gx+z/G8u0VHR71IQOQQe4cc+EpAsbbfYlpzuvH9rz+dBL4dmMWDja2FJfPzqiQU9TjBRAWkA5Ytx9wLlhVwlwLnns9fKzCQ82XPqkEWhK6rfWDLJywlB2whaELW592UNRhzvX+xwxj0rDPs0+xqI5bbQ7TkXHjtSDzz/bwAz020jE7DYf35hD4y4CYClrw8Sn2sbwrTzrH4HUyzxnjC+qwe7W1CT93XVkAYFU/VcYLygzBNwIHd7wilg0TiYSViUMcjhzrsA8PBmW42kD2f/WZZzjD+KxaO1ENxBaVbaqopq6w/oTtCcbTkhbYrh/LLD14GsCoQVX2RLse6Fch/qCwp4r26q1D0eDABmPKyp46p4YBQrMVS0QIq8LAoEgF/SSqkUXUhWT+qWtAedknOWN/bXSsvPsKsST1/TkFsyz3AOw5D7ZYTrAP1sJR0wN4cFOBSrRf+S9c9TcPJUILT8/GvxrWb9yNcT4L3MUz5t0sBT1YlWi1dhjPFrrKIMh+CGdtEXAOTgR9MqYWXtjJqBW+XSnUfvpwHPL2+JnVUUwrCzJxVVm86lapyYoDyj/Ddaz3nw8Gof32G4c9BCuLh0bYYfk+FUeKqBg9UDKDQ5zaR4k/3obCh3sHRQcaZZNIGcu0s3ibZU2qB93S+82DuIFiAlhDnNuYxr5+8LdE0InQpbD8d9x5QSxAZ0It0gaGlgfX5MI4TTklRTocYZUjWNLvj7k4PkJ3xbxpo1XY9dX5e+PSWFAvus2HMNuivzJgLyiiv0fCLIAKVKr/wFGjV5VyXqiDdwvyFItvBYtmnZPzxlSgvmN9wCDAsiN09snZzvKZ3SbqzlTOkD0Ri7K6vjnAce+NvQk296vVDyEAi6ECDVJj9gSnr2ZA+6wtbKqvWjvztoU95hWi0fa9VSqRtAriZrCrqYTpw0xgH+3uA8hTgD5zA1fnMv/7Jm5eM52ugVoMvbcq3w/+szZXJNywS+Kngt6UumMob4WbqAJ4nZnPlHR5ODl4bU7GnToj5o4MvFXnaTFrJ7vDWhCVtoybs08aM4jgCztmGFyeXnc0uxme1myhWOu87ksmfdD6u8HlWeJhrnkcwd/jQaI97+gFNe2aJ7MVF26nvVXBMLsiJdY/Zc12b8dYjuwF7xkVa5n2iYkEXzUYJTfimLUqydu64k0k8258dHjSX5liSZm0dj/CAE9uly4DrP+wZGTMFGD3iwlTOPcW62z6YYHcGPNCcMveeGQ2Ryi++TM+kMkT6zZT5UnuL04ENjWjrBFYZtzjy1QhNsx5uXPCFhY6mDlAHqCEqBNVyjFn9PxJ4RlkN4sI/vPDTC2K3gHBoW49ZwB0kG7JHR/mbey8O0n3H2XDMz+z80gl1kZyBuvIeTjSk4HFe8XKW81WB1jUrriTUBjtFnsVJVctuRhr3VaKph1z5WoKXCte/whcAIXhWpTXcC8He584PREUN8HKJ62RVh6lnaw2uNbhPrfdBS+h0uwEg+KMKQ6cX8BowfGaMaD219G4Nb5wJCBQzrUVebNK1DbIHZVcdNUT80gN5aijSdRY5C+VgGLuGXDPovo/r69/pitPExQVy8o13G5bsSqskSdgUbQ/2OHPYbcbSPlgvuKtJa4bRI0zwgKRwzxnMtcQktbluDZL9YP1q/40Rsbnh+7IA8S/25O5hT2RehqcRAFYsop5lw2kZdfEmSAN4032QoGcBYGDByKHTQjOejleHNwU3iQnCgWMnHTXDa7CPkoVDPsarurnhriEXCQxjxK2wC3Ob+2xh37eFhHOemCQIAblCedHj3uCferfCBDiAIfAO8Li7GnBtOqfRCcHdBi1BsRafWkfRoUcwU6hBu75pTJcx78JJvq0YaEN7nXL2tV3V5yBZWp7c1yf1oKqz4uzXzXaXPWXnEifRAPNgSvxTTsno0YbVqNr6/iyEz6fdbnSvdqg90Lz3uSAKvfFl1C+KynQb6c5ejkDEY0zQCBxeBgJLeMg1glhQr934aZRBd/y/a1BcHzE/aZpmfWlVolAZ1NbScDOZZiCtxK28gOmXmATnZAYyIf7JEyEMbihGmO5Tk5fzFS3BtHZvMDnrEUEPIIElPdCy50gZvQQcS9XhE8XOoNTYPFk2XRwVmO5wPHG0wCUuaKEyUG6yU/l143o9KoMPeQeRj9X2PKrq1rzMnVcKrhxkk+58zkXkmQ71ITQjFGCCXMLkAU9qnc2cvs7I3iWLkrbhcwScemTDG6jd1KgIrL9EZi4xAeCAegDoK2S20TEs8UUyrMRbxkiklxkMBop0/cEjr0JeT0aLYzvQP0/LNZTctN5+g3eHeV+jqqF+/tdi41i+Kf8DRHNPzrI/A8RJf3WxxRrm3mfavhkvl2wQXOiezLPqoDkKWRo9JBnWVfnOdjfVVFG2pAQEwNSYQjr3J/BZp6QF3OP/R9prVCgDnQvrTDpaEJ587KyMQ49aS7D5r8xtuYF67RHBaxkDH03b5JLE64DF5LlGDTWGgvEJO8EH9d/64P2Ejqc202DK8sg4DF0hrbQFUNUSgVxkRraGXr1S+U7E6gTXGnpXT1TkgGHbcfavq55pk9nOS6JC+h/nZDlLSG1Cqxkr6sElL9qVFVqZ9mUt9OAAJAVvyrtpzkKSF2OMLzgkCEfv3yvBPcvnag3wuY3imlXkDSi5wIsLD3a7TFPKSyqtchwnboyvcS5izGOIuXGe9r3ooSaAu7qXBeFZNRgVTQ0tVdZZlFfgb7AJzK4DDr3ND+BOikQPSpnjQT82zdWZpkncp/26wp8TbSKbu4p/uuF7izbYNeMOFSDychVn85dyV8xWD7EKZISbq9cIaNA0Ccjo70u2Hhm1qxc97b5WeaXlJuY4PzQlmEPRJHyiQMHASOBkXK8wu7u6t5CmJqNZ0ga1grV+Dp+Aitvj+2Jh8rZ5qycnBqRr++WYVAr5BPvwVs6xIHv0R8ZV+shQP5v3ojj8UlsSyp9eWd89y9FkuoHduwBNUUvl4nS1bVBSZZQuaOHQD18R47sQgWbRb52s9c13lpmlyjjPwdNu2z12lRNijjHQu7lbY5hO5bSNHsR9Zo0JZhimGWteNCgzXBX6Jse9RFnR9POsri5ThErvgeJUe7t2WdIkTOzIyO6seZ9Q7YHMpQGxpUTWcPHzFQSCNW8VbDJbpZn+DnTdObdzwYlkiwU1G+g2UOi3ATnatoHcz3I8//vwFg1dPKLLhPZMAi62Fy3p370CuKiWPagAYhc+khTdgv2GgjVLRkmqBm53gLzeYjS++06jRz/HHBukRHsKkXjvb/f1eDecc9TYQUU9xTz/UI2ap0JEvLtXKQRB63pUUYzKlulcrDFUg51YdhlwpFKTU5RvPPp4LdyytC/zrjhuCfSEpSmdlIjLXLdRUESjKRC31OTS+tuACDfsGbVqKJa/LwgjJ51eYZOnAGuatSb9+96k8iyGS2dKbhB/y0Zz1zFJrBokpe+u/ZoRA2s9X1Htkl0w58ZQmWfyHD4IRYy82x9zzbQKcwJPCKS+2n7HN/MWuNKxCgcmWg1kdf+FWvvacx4orW9vGKVZsxy8+HE+WhmVuZrnwZAOQ5aQ/Zk3ksM4a/wpPvGVh0Yz3zC/W6YOjhS11A5INNRsiTn5TOf8Br4PHC0uaTIZhf54rD5p3degpmjO52Bqa10Fcbztj+QPI6Uo/07w8Ax4iQuwwyObiBw5KSYeB7YWDxWDlX9f0FWk9GKiyN42e7L7vhgD+RJrw03weslj06xf6LcKLgT2PUUl8jOw+lUzmsQ1jhPg23KbcSkIlfiGLNiRclVjZhTVv0NIn6UtnoGwsKj5y9Z06I3NRTjdTJ35CNLdRsxybXyELhawBfdus+EQ84IMIPoKhTQn1dP/Lwp3YB5m7Wqw3JGd6YWn0jB5Yc6jnXCqDl5Vmh7UP2mbeZZowCPY5hvXUVf6mD3uJL9t90TQe0S5/PAl1NHh+aPXVJ9dya3zQHDpYBVPEIZ6xfDB+we41bv41rkuvhlWGnV446CdNL8EYEnVoaYeijlLjQ7zb+usPsne4L+405vKUBD2gPAQd79ooGX2hugFZI2nR62io0SnrBtC/p3e3HOckUG8EC5B3LVT6TOXSE8SzHkSAgHqsNdGUuhZyjAHHhvg+Z5oZyQnk4zRNkagTaQGZmE9jPFPpZcJW37R4gYRmY7K9/drVCEeUOVqzK21gXzHm8eVfmc1N7QKWIPA0Lnob3738sHwoBU5esDTgmiSYXRUkD8QykW5r31ipCK6ZApiriGxGF1vWPM/gcv2ucqHFoFH1Ms0SkgnIfN68ZOJIi5S/5+mL45zjtq00oClX8zNycM9U4M5pt5DOu0G94Vp5zwzW+Y+2kSrb9BW3mqh6EeO8Oe+X7U0tD4QgnCXftWZTPDiXhBerpXpe/z7U6GMyCRozlFFbN0Gsb06T1jZ2q0Iqc24F2mYOUqDSRSlN27+tXdJJYH1CrIduehirD2xpGIKiqHOMbydsA6yVR9b/NCkmEHrFonkEXrGC+uvfA0nGmKj5xmVKvIoB+ZYfb+hkynnRDQknWv/P01aUUuCkp46ApPmswc3Chth8K3usaOurFyj6X5cjuyGhp8WS6U/VCJ7vg6MBb4ct13HXf6ucKCpJScXbcqJZt4C0hwDTQdi7NwTmgJyI1mA4UFh5ipVKLZuTfndXhIeCIgsL5RVYQaQImjE2QMwbYZCZNynNWN6VZKN66+EbaNVnE0XfG9I1mL3JJT4Duk8GFI0gsbRlqtHCoWLMw9p8EcsyNzbCKmvDluraQQa8MnaGyGP71SpLYSXLlUsHYfG6GpAPvwKAK1UgHAAAAAAVD3lAigx/03F7sz6h+WgA7dvule2AowD7+qC77fgYd5Dc4yLGbs2AcAEvn/Ku7eFwOS8ZTH4mmom2yQA2bhmJdXhh7SwQRB7b53RB9DfJLNObVVTbpwLAvW5LeCsBg7A+cJkBHL+tP1KxMAwBlCw3ZbKs8i8SPDqjCB4AUHIP8yzg8qT/W2wltEeHhxn0HBK3IIb9G3vCk4ysmOa1kGmoQ2nVi7kZkdksWNrmz3zUAAAAAAAAAAAAAAAAAAEFkqpTP/il9a9QY5C+9ki8nOYasolm6wam/85WB2AH56F/D5zpv7QunbOzwu/1/eZv+Yb/VaXqxq/3T5fuPkjy20jbYTNRIRAEY08qvZEX9Y2ibiU4S8kw/guw7RE8rHCRgFvD+QjyoBGCTrDGEo6/Gv8UOpawK5yuzfeylBkVpTZ7NNCR8gLk5SpJbmN4KROAYqpvweMv/MW7Wdx9CDBxtTN0+sQKDvPpESA/CT0A5tHACshoysVJvutA1ScXuvAIxOUKpgbIv8eIx+SZTLThA0If51l8u8kMILJtnnu5KaaxAbbdd6lfOijMqBXxcJ7lzJye3CM7hTqXacK1dsiGgmuAqq58WEteJNi9eavgBxAjf0qJFL98LJwJuo3rte6d+Px2YN2ltpDdOz0Ya4vCWZ6s+9orOyvOiPozC/GmkbJQYVWo++0e2zRYh2F2d8eXWUmP4Cy0H8UTPZxK4s2Z0aYfUbNILLkR/836GRTsW6099Vy5L3jwvl8NJiJ11ImCoiOYpnCjHLo0ryEDPV1jkz9nim6u/s1QED3GA+fffNSXu46qqrkQh65JRrvPtF95wUIXJLI47DoVajK45kP47KHf/UZPTZwaNOuHKavOF8F8lSYkNgxGpgQZnjxjyfqIpwjx1n1qGd+EnJd+iiT2+PG3UARLcOQ3exIrTyGMGRi7AGxDiXSIY/VuRPMLoA6x1Ac/1FDXaNVyhIFysQdQQEIvwEW1gMc2hAu+bKgDwF96e6y2LdIv/bWX40DaQ+P2rG5gUjgMkQBN2+SOu5N8kVeP2ufsgknjZFeRidS29rNL8s37iQNFnbTKNUl1r4ooGHc5ooKYPfLTeZC8OZfjenstUmy0tEQ0NrZnIWGMsSLaP/Epys6XD6IjbOq7lBC6KjZoEehiF1JcjJza0GB6lZvPqI11rmtDDelTJu0Bm/lBUjXXFK9BgwNNLSjb9On5qBlW5FVOV1D7hFRVzHoHYgJct1IJtkOibhr7yhtsBbAoCHjJK/I0OygWGKvrYTIBT4GRJCEdI4ZzfwwgD7FdVDYv3IlLmAAAAA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-
-[[27张宇基础30讲高数.pdf#page=9&rect=87,301,212,323|27张宇基础30讲高数, p.9]]
 
 ## 函数极限与连续
 
@@ -18,17 +16,12 @@
 
 ## 基础内容精讲
 
-![](images/74a100db082d274876e036335671f14987584bf05452ab58d09a168c36f791ab.jpg)
-
 ## 函数的概念与特性
-![[27张宇基础30讲高数.pdf#page=11&rect=144,533,291,628|27张宇基础30讲高数, p.11]]
-
-![](images/e89058068960f0d960b6817ae94b089b8823c71b8977d391e32ba0a7edf88ef1.jpg)
 
 ## 1函数
 设x与y是两个变量，D是一个给定的数集，若对于每一个x∈D，按照一定的法则f，有一个确定的y值与之对应，则称y为x的函数，记作y=f(x)，称x为自变量，y为因变量，称数集D为此函数的定义域，定义域一般由实际背景中变量的具体意义或者函数对应法则的要求确定，称 $\{ f ( x ) { \big \vert } x \in D \}$ 为值域.
 
-## 注单值函数与多值函数
+## 注：单值函数与多值函数
 
 事实上，上述定义的函数是单值函数，若给一个 $x _ { 1 }$ ，对应一个 $y _ { 1 }$ ；给另外一个 $x _ { 2 }$ ，对应另外一个$y _ { 2 }$ ，这叫一对一[见图1-1(a)].若给定 $x _ { 1 }  ,  x _ { 2 } ( \ : x _ { 1 } \neq x _ { 2 } )$ ，它们对应同一个y，则称多对一[见图1-1(b)]，所以函数可以一对一，也可以多对一，这叫单值函数。
 
@@ -94,7 +87,6 @@ $$
 注本书所讲的知识是全面的，对题目的把握是准确的.从范围上、广度上讲是涵盖整个考研大纲的；从深度上讲，掌握我说的题目的难度就够了，达到这个难度，考研数学就能解决了．比
 
 这个题目的难度低，不行；超过这个题目的难度，不需要！
-
 ## 2反函数 →前提：符合铅直画线法.
 
 设函数 $y = f ( x )$ 的定义域为D，值域为R.如果对于每一个 $y \in R$ ，必存在唯一的 $\boldsymbol { x } \in D$ ，使得 $y = f ( x )$ 成立，则由此定义了一个新的函数 $x = \varphi ( y )$ ，这个函数称为函数 $y = f ( x )$ 的反函数，一般记作 $x = f ^ { - 1 } ( y )$ 它的定义域为R，值域为D.相对于反函数来说，原来的函数也称为直接函数.以下两点需要说明.
@@ -109,6 +101,9 @@ $$
 
 ## 注（1）单值函数（符合铅直画线法）才谈反函数
 
+![[考研/math/file_other/27张宇基础30讲高数.webp]]
+
+[[27张宇基础30讲高数.pdf#page=15&rect=69,465,445,588|27张宇基础30讲高数, p.15]]
 （2）有反函数的函数不一定是单调函数，比如
 
 $$
diff --git a/考研/math/003_第2讲.md b/考研/math/003_第2讲.md
index 5399528..74c70a1 100644
--- a/考研/math/003_第2讲.md
+++ b/考研/math/003_第2讲.md
@@ -1,4 +1,5 @@
-## 第2讲
+[[27张宇基础30讲高数.pdf#page=84|27张宇基础30讲高数, p.84]]
+## 第2讲】
 
 ## 数列极限
 
diff --git a/考研/math/27张宇基础30讲高数.pdf b/考研/math/27张宇基础30讲高数.pdf
index 8ba9a0a..3507a83 100644
Binary files a/考研/math/27张宇基础30讲高数.pdf and b/考研/math/27张宇基础30讲高数.pdf differ
diff --git a/考研/math/file_other/27张宇基础30讲高数.webp b/考研/math/file_other/27张宇基础30讲高数.webp
new file mode 100644
index 0000000..05a7695
Binary files /dev/null and b/考研/math/file_other/27张宇基础30讲高数.webp differ
diff --git a/超级备忘/机器学习/机器视觉.md b/超级备忘/机器学习/机器视觉.md
index 6310aeb..6b12fed 100644
--- a/超级备忘/机器学习/机器视觉.md
+++ b/超级备忘/机器学习/机器视觉.md
@@ -6,3 +6,5 @@
 
 偏振片消光
 
+灰度函数
+直方图均衡化