# 学习笔记

**Repository Path**: aichisha/study-notes

## Basic Information

- **Project Name**: 学习笔记
- **Description**: 这是我自己整理的一部分笔记
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2026-06-03
- **Last Updated**: 2026-09-15

## Categories & Tags

**Categories**: Uncategorized

**Tags**: 学习

## README

# Study Notes

> Personal knowledge base covering mathematics, mechanics, robotics, AI, computer science, control systems, physics, and more.
> **~300+ files**, managed with Obsidian.

---

## Knowledge Map

```
Mathematics → Mechanics → Robotics → AI
    │            │            │
    ├─ Analysis  ├─ Statics   ├─ DH Parameters
    ├─ Algebra   ├─ Dynamics  └─ Modern Robotics
    ├─ DE/ODE    ├─ Materials
    ├─ Stats     ├─ Fluids
    └─ Optim     └─ Spacecraft

CS Fundamentals → AI/ML/DL/RL
    │
    ├─ C++ (21 chapters)
    ├─ Python (5 chapters)
    ├─ R (3 chapters)
    ├─ MATLAB (50 chapters)
    ├─ Data Structures
    ├─ Eigen (16 chapters)
    ├─ CMake, Git
    └─ Algorithms (Luogu)
```

---

## Getting Started

### Recommended Reading Order

| Priority | Topic | Path |
|----------|-------|------|
| 1 | Mathematics | `数理基础/代数/Linear algebra.md` |
| 2 | C++ | `计算机类/C++学习/` (01-21) |
| 3 | Python | `计算机类/python学习/` (01-05) |
| 4 | MATLAB | `计算机类/MATLAB学习/` (01-50) |
| 5 | Data Structures | `计算机类/数据结构.md` |
| 6 | Eigen | `计算机类/Eigen库使用指南/` (01-19) |
| 7 | Deep Learning | `人工智能/深度学习教程/` |
| 8 | Reinforcement Learning | `人工智能/强化学习系统教程/` |
| 9 | Control Theory | `自动控制原理/控制理论教程/` |
| 10 | Robotics | `机器人学/DH参数法/` + MATLAB robot series |

### Using Obsidian (Recommended)

Open this folder as an Obsidian Vault:
- **Graph View**: Visualize the knowledge network
- **Start**: `00-知识索引.md`
- **Search**: `Ctrl+Shift+F` for any concept

### Compiling LaTeX

```bash
cd 人工智能/深度学习教程/LaTeX
xelatex main.tex && xelatex main.tex
```

---

## Key Tutorials (Markdown)

| Tutorial | Files | Content |
|----------|-------|---------|
| **MATLAB** | 50 | Basics → Dynamics → Control → Robotics → Simulink |
| **C++** | 21 | C foundations → OOP → STL → VS/CMake → Student Manager |
| **Eigen** | 16 | Dense matrix → All decompositions → Geometry → Practical |
| **Deep Learning** | 12 + LaTeX | Linear algebra → CNN → RNN → Transformer |
| **Reinforcement Learning** | 6 + LaTeX | MDP → DQN → Policy Gradient → PPO |
| **Python** | 5 | Basics → Functions → Data structures → IO → Exercises |
| **R** | 3 | Data types → dplyr/ggplot2 → Statistical tests |
| **Linear Algebra** | 7 | Vector spaces → Spectral theorem → Jordan form → SVD |
| **Abstract Algebra** | 5 | Groups → Rings → Fields/Galois → Modules |
| **Control Theory** | 12 | Classical → Modern → Nonlinear → MPC |
| **Data Structures** | 1 (1696 lines) | Lists → Trees → Graphs → Search → Sort |
| **CMake** | 2 | CMake basics + VS Code integration |

---

## External Resources

- Deep Learning: [RethinkFun](https://www.rethink.fun/)
- Eigen: [libeigen.gitlab.io](https://libeigen.gitlab.io/eigen/docs-5.0/)
- MATLAB: [mathworks.com](https://www.mathworks.com/help/matlab/)