In this post, I will summarise several topologies established on the product spaces of \(\mathbb{R}\), i.e. \(\mathbb{R}^n\), \(\mathbb{R}^{\omega}\) and \(\mathbb{R}^J\), as well as their relationships. Topologies on product spaces of \(\mathbb{R}\)…
Proof of Theorem 20.3 Theorem 20.3 The topologies on \(\mathbb{R}^n\) induced by the euclidean metric \(d\) and the square metric \(\rho\) are the same as the product topology on \(\mathbb{R}^n\). Proof: a) Prove the two metrics can mutually limit ea…
Theorem 20.4 The uniform topology on \(\mathbb{R}^J\) is finer than the product topology and coarser than the box topology; these three topologies are all different if \(J\) is infinite. Proof: a) Prove the uniform topology is finer than the product…
[转载请注明出处]http://www.cnblogs.com/mashiqi 2017/04/15 1.$\text{p.v.}\,\frac{1}{x}$ 因为$(x \ln x - x)' = \ln x$, 所以$\int_0^a \ln x \mathrm{\,d}x = \lim_{\epsilon \to 0^+} \int_\epsilon^a \ln x \mathrm{\,d}x = \lim_{\epsilon \to 0^+}(x \ln x - x)\big|_\eps…
The parallelogram law in inner product spaces Vectors involved in the parallelogram law. In a normed space, the statement of the parallelogram law is an equation relating norms: In an inner product space, the norm is determined using the inner produc…
https://www.quora.com/How-do-I-learn-mathematics-for-machine-learning   How do I learn mathematics for machine learning? Promoted by Time Doctor Software for productivity tracking. Time tracking and productivity improvement software with screenshots…
At the beginning, the difference between rank and dimension: rank is a property for matrix, while dimension for subspaces. So we can obtain the rank of A, which reveals dimensions of four subspaces(2 from A, 2 from AT). Important fact: The row space…
以上我們談了一些 邏輯的基礎,接下來我們會談一些 數學的基礎,也就是整數與實數系統.其實我們已經用了很多,非正式地,接下來我們會正式地討論他們. 要 建構 實數系統的一個方法就是利用公理跟集合論來建構. 首先我們需要從集合論出發,定義在 set $A$ 上的 二元運算子(binary operator): Def. $$f: A times A rightarrow A$$ 我們在描述一個二元運算子的時候並不會如同以往的函數一樣, $f(a, a')$,而是會把運算子寫在中間, $afa'$.一…
目录 概 主要内容 符号说明 的俩种表示 kernel orthogonal regularization orthogonal convolution Wang J, Chen Y, Chakraborty R, et al. Orthogonal Convolutional Neural Networks.[J]. arXiv: Computer Vision and Pattern Recognition, 2019. @article{wang2019orthogonal, title=…