高斯牛顿法: function [ x_ans ] = GaussNewton( xi, yi, ri) % input : x = the x vector of 3 points % y = the y vector of 3 points % r = the radius vector of 3 circles % output : x_ans = the best answer % set up r equations r1 = @(x, y) sqrt((x-xi(1))^2+(y-y
2ed, by Timothy Sauer DEFINITION 1.3A solution is correct within p decimal places if the error is less than 0.5 × 10$^{−p}$ .-P29Bisection Method的优点是计算次数(step)是确定的(interval<精度).后面介绍的算法的interval是不确定的, 所以什么时候结束计算呢?不知道.所以定义“stopping criteria’’来决定什么时候结束
2ed, by Timothy Sauer DEFINITION 1.3A solution is correct within p decimal places if the error is less than 0.5 × 10$^{−p}$ .-P29Bisection Method的优点是计算次数(step)是确定的(interval<精度).后面介绍的算法的interval是不确定的, 所以什么时候结束计算呢?不知道.所以定义“stopping criteria’’来决定什么时候结束
< Neural Networks Tricks of the Trade.2nd>这本书是收录了1998-2012年在NN上面的一些技巧.原理.算法性文章,对于初学者或者是正在学习NN的来说是很受用的.全书一共有30篇论文,本书期望里面的文章随着时间能成为经典,不过正如bengio(超级大神)说的“the wisdom distilled here should be taken as a guideline, to be tried and challenged, not as a pra
OpenCV has function matchTemplate to easily do the template matching. But its accuracy can only reach pixel level, to achieve subpixel accuracy, need to do some calculations. Here i use a method to make template matching reach subpixel. First use mat
这个知识点很重要,但是,我不懂. 第一个问题:为什么要做正则化? In mathematics, statistics, and computer science, particularly in the fields of machine learning and inverse problems, regularization is a process of introducing additional information in order to solve an ill-posed p
