FGM-plate-k

Face Verification System With DFT

很好的一本书，适合初学者，尤其对想要用matlab实现与计算机互动的人很重要。(A good book is suitable for beginners, especially to want to use matlab and computer interaction people is very important.)

Just a few functions used in my other toolboxes, for computing MSE and PSNR and some other less common image quality metrics.

说明：  灰度变16进制包含了多种功能是各种代码中必要的一步(Grayscale variable hexadecimal system contains many functions, which is a necessary step in various codes.)

matlab常用命令查询，方便新手入门matlab(matlab command queries used to facilitate the Getting Started matlab)

Simplified Bulirsch-Stoer method for intergration of y = F(x,y).

It is another code for simulating heat loss

基于matlab的动画制作详细教程（共27页）(animation tutorials based on matlab (27pages))

深度神经网络在函数近似中表现优越，然而需要从头开始训练。另一方面，贝叶斯方法，像高斯过程（GPs），可以利用利用先验知识在测试阶段进行快速推理。然而，高斯过程的计算量很大，也很难设计出合适的先验。本篇论文中我们提出了一种神经模型，条件神经过程（CNPs），可以结合这两者的优点。CNPs受灵活的随机过程的启发，比如GPs，但是结构是神经网络，并且通过梯度下降训练。CNPs通过很少的数据训练后就可以进行准确的预测，然后扩展到复杂函数和大数据集。我们证明了这个方法在一些典型的机器学习任务上面的的表现和功能，比如回归，分类和图像补全(Deep neural networks perform well in function approximation, but they need to be trained from scratch. On the other hand, Bayesian methods, such as Gauss Process (GPs), can make use of prior knowledge to conduct rapid reasoning in the testing stage. However, the calculation of Gauss process is very heavy, and it is difficult to design a suitable priori. In this paper, we propose a neural model, conditional neural processes (CNPs), which can combine the advantages of both. CNPs are inspired by flexible stochastic processes, such as GPs, but are structured as neural networks and trained by gradient descent. CNPs can predict accurately with very little data training, and then extend to complex functions and large data sets. We demonstrate the performance and functions of this method on some typical machine learning tasks, such as regression, classification and image completion.)

动态规划算法的顺序（前向求最小值）算法的matlab实现以及一个算例，还有一篇参考pdf文献，适合初学者，有我个人的一点注释(Dynamic programming algorithm for the sequence (prior to seeking the minimum value) algorithm matlab to achieve, as well as a numerical example, there is a reference pdf document, suitable for beginners, there are my personal notes that)