- 深度学习:卷积神经网络从入门到精通
- 李玉鑑
- 261字
- 2023-07-26 11:56:27
2.2 矩阵运算
如果矩阵A =(aij)m×n,其转置矩阵B =(bij) = AT的所有元素定义为
![](https://epubservercos.yuewen.com/E65590/11298848104511106/epubprivate/OEBPS/Images/figure_0031_0007.jpg?sign=1739130883-L2EoAW2i6Fdu2FHSqG1BSyO1YBID0lx7-0-42b312e31c1f2da3c22c180960c24531)
如果矩阵A =(aij)m×n,其180°旋转定义为
![](https://epubservercos.yuewen.com/E65590/11298848104511106/epubprivate/OEBPS/Images/figure_0031_0008.jpg?sign=1739130883-6CdkHJtHf6DWQ1TVZelzZQYvnG4g3I6F-0-212f9ac3314d27660958b192e9f0a0a9)
给定两个矩阵A =(aij)m×n和B =(bij)n×p,它们的乘积C =(cij)m×p= A·B = AB的所有元素定义为
![](https://epubservercos.yuewen.com/E65590/11298848104511106/epubprivate/OEBPS/Images/figure_0031_0009.jpg?sign=1739130883-mRR5UpqADGprSUdCRzloWcxT27cYNYIL-0-3f142d3672dad096d38412141ef44c7f)
给定两个矩阵A =(aij)m×n和B =(bij)m×n,它们的加法和减法定义为
![](https://epubservercos.yuewen.com/E65590/11298848104511106/epubprivate/OEBPS/Images/figure_0031_0010.jpg?sign=1739130883-EFczpFjirLfLlWLPebWzmfpYdnh8eNs0-0-3ba401189914553e5875d9f179102b56)
它们的阿达马积(Hadamard product),又称为逐元素积(elementwise product)定义为
![](https://epubservercos.yuewen.com/E65590/11298848104511106/epubprivate/OEBPS/Images/figure_0031_0011.jpg?sign=1739130883-fRQvmUAklFhKPTmzmczxWpqw67GZNlpk-0-f96f3b1f0312f1b173380c825e3aea8f)
给定两个矩阵A =(aij)m×n和B =(bij)p×q,它们的克罗内克积(Kronnecker product)定义为
![](https://epubservercos.yuewen.com/E65590/11298848104511106/epubprivate/OEBPS/Images/figure_0032_0001.jpg?sign=1739130883-AB9H9RBK1SOA0KYJNmvvtQkaube1zPJy-0-59a6b54d0d073b3717f5b2c058cd193d)
如果x =(x1, x2, …, xn)T是向量,那么一元函数f(x)的逐元向量函数(elementwise vector function)定义为
![](https://epubservercos.yuewen.com/E65590/11298848104511106/epubprivate/OEBPS/Images/figure_0032_0002.jpg?sign=1739130883-4KNgbbCaOTYw8Itf98mbEDocBr9g3sai-0-4e9111beb31e476405ed2e728d4cc274)
如果X =(xij)m×n是矩阵,那么一元函数f(x)的逐元矩阵函数(elementwise matrix function)定义为
![](https://epubservercos.yuewen.com/E65590/11298848104511106/epubprivate/OEBPS/Images/figure_0032_0003.jpg?sign=1739130883-7KEVjBrf6G1Xw8vHQ2ndJbBfgqgIjXek-0-673c35eae141faba0c701cf6c109fdcc)
逐元向量函数和逐元矩阵函数统称为逐元函数(elementwise function)。