麻省理工算法导论课程的教师讲义，经典之作，算法必看

这是MIT【本科生课程】6.006详细指导文档!

通过这个文档我们能大概了解我国的计算机教育跟国外的差距，好师夷长技以制夷

包含很多基础的数学知识，尤其是英文的，可以提供基础数学英文术语，非常好的资源！

线性代数是数学的一个分支，它的研究对象是向量，向量空间（或称线性空间），线性变换和有限维的线性方程组。向量空间是现代数学的一个重要课题；因而，线性代数被广泛地应用于抽象代数和泛函分析中；通过解析几何，线性代数得以被具体表示。线性代数的理论已被泛化为算子理论。由于科学研究中的非线性模型通常可以被近似为线性模型，使得线性代数被广泛地应用于自然科学和社会科学中。

2-作业 2#了解iic协议，以及PCA9685如何通过IIC协议控制多个舵机 L2-作业 3#针对课程内容，提出三点对于课程的疑惑和建议 L2-作业 4#了解目前市面上几款常见的四足机器人的特点和区别、包括波士顿动力Spot mini，2-作业 2#了解iic协议，以及PCA9685如何通过IIC协议控制多个舵机 L2-作业 3#针对课程内容，提出三点对于课程的疑惑和建议 L2-作业 4#了解目前市面上几MIT 猎豹款常见的四足机器人的特点和区别、包括波士顿动力Spot mini，MIT 猎豹、宇树科技、蔚蓝这几家公司的产品，并写介绍总结文档MIT 猎豹、宇树科技、蔚蓝这几家公司的产品，并写介绍总结文档

美国麻省理工学院电路与电子学讲义，非常简明实用

rddata.m -- MIT-BIH ECG 信号的数据读取Matlab程序 MIT-BIH ECG 信号的数据读取Matlab程序，能够读取MIT-BIH数据库 .atr、.dat、.hea三种文件的数据，根据这些数据计算出实际的心电信号值，并绘制出信号波形。

这是卡内基梅隆大学的公开人脸测试集。测试集共分四个文件夹，分别为测试集A、B、C和旋转测试集。由于大小限制，因此将四个文件夹分开上传 The image dataset is used by the CMU Face Detection Project and is provided for evaluating algorithms for detecting frontal views of human faces. This particular test set was originally assembled as part of work in Neural Network Based Face Detection. It combines images collected at CMU and MIT. Please give appropriate acknowledgements when you use these test sets. In the lists of files below, you will find references to Test Sets A, B, C and the Rotated Test Set. Test Set B was provided by Kah-Kay Sung and Tomaso Poggio at the AI/CBCL Lab at MIT, and Test Sets A,C and the rotatated test set were collected here at CMU (by Henry A. Rowley, Shumeet Baluja, and Takeo Kanade). In [Schneiderman and Kanade, 2000] and [Schneiderman and Kanade, 1998] we refer to the combination of test sets A, B, and C as the "combined test sets of Sung and Poggio and Rowley, Baluja, and Kanade." In [Rowley, Baluja, and Kanade, 1998] we refer to the combination of sets A, B, C as "test set one" and in [Rowley, Baluja, and Kanade, 1997] we refer to it as the "upright set" as distinguished from the "rotated set."

这是卡内基梅隆大学的公开人脸测试集。测试集共分四个文件夹，分别为测试集A、B、C和旋转测试集。由于大小限制，因此将四个文件夹分开上传 The image dataset is used by the CMU Face Detection Project and is provided for evaluating algorithms for detecting frontal views of human faces. This particular test set was originally assembled as part of work in Neural Network Based Face Detection. It combines images collected at CMU and MIT. Please give appropriate acknowledgements when you use these test sets. In the lists of files below, you will find references to Test Sets A, B, C and the Rotated Test Set. Test Set B was provided by Kah-Kay Sung and Tomaso Poggio at the AI/CBCL Lab at MIT, and Test Sets A,C and the rotatated test set were collected here at CMU (by Henry A. Rowley, Shumeet Baluja, and Takeo Kanade). In [Schneiderman and Kanade, 2000] and [Schneiderman and Kanade, 1998] we refer to the combination of test sets A, B, and C as the "combined test sets of Sung and Poggio and Rowley, Baluja, and Kanade." In [Rowley, Baluja, and Kanade, 1998] we refer to the combination of sets A, B, C as "test set one" and in [Rowley, Baluja, and Kanade, 1997] we refer to it as the "upright set" as distinguished from the "rotated set."