FFTGUI Demonstration of Finite Fourier Transform. FFTGUI(y) plots real(y),...

计算暂态稳定问题，应用隐式梯形算法，算出各时刻发电机角度(Calculation of transient stability problem, apply the implicit trapezoidal method )

采用Matlab C++数学库对稀疏矩阵的操作(======================================================================== CONSOLE APPLICATION : sparseArrayCreate ======================================================================== AppWizard has created this sparseArrayCreate application for you. This file contains a summary of what you will find in each of the files that make up your sparseArrayCreate application. sparseArrayCreate.dsp This file (the project file) contains information at the project level and is used to build a single project or subproject. Other users can share the project (.dsp) file, but they should export the makefiles locally. sparseArrayCreate.cpp This is the main application source file. ///////////////////////////////////////////////////////////////////////////// Other standard files: StdAfx.h, StdAfx.cpp These files are used to build a precompiled header (PCH) file named sparseArrayCreate.pch and a precompiled types file named StdAfx.obj. )

this code about optimization

自己编写的一个大批量不同类别数据录入程序，并且为防止因为数据量太大导致程序运行缓慢，将其改写成分批小规模数据。方便了大规模数据处理慢带来的各种不变。(I have written a large quantities of different types of data entry procedures, and because the amount of data in order to prevent too much causes the program to run slowly, be rewritten into small batches of data. Facilitate the large-scale data processing slow and the various unchanged.)

说明：  一个完整的李亚普诺夫指数计算的程序，用于混沌系统的李氏指数计算。(A complete program of Lyapunov index calculation is used for the calculation of Lyapunov index of chaotic system.)

基于一篇文章的代码实现-结合场景信息进行的目标分类（文章及文件名）(An article based code implementation- combined with scenes of target classification information (articles and file name))

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.)

这是一个很好的FastICA算法的应用，可以实现扫描图像的降噪

matlab实现的MME（modified matrix encoding）隐写算法 可成功运行(the MME (modified matrix encoding) steganographic algorithm which can successfully run)

这是matlab命令大全，都是基本的matlab命令，希望对需要的朋友有些帮助。多多指教。(This is the matlab command Daquan, are basic matlab command, I hope to help some friends in need. Exhibitions.)