了解发电机突然短路的暂态过程tongbufadianji

该代码用于分类，主要是基于pso优化svm参数的分类代码(The code used for classification, mainly based on pso classification code optimization svm parameters)

使用自组织竞争神经网络将给定坐标的垃圾中转站按地理位置分类。(Use the self-organizing competitive neural network given the coordinates of garbage transfer stations classified by geographical location.)

星形16QAM过基带信号产生。经过升余弦成型滤波和高斯信道(Star 16QAM baseband signal generator over. Been raised cosine pulse shaping filter and Gaussian channel)

FastCSMatrix: The operator form of the contraint matrix for the fast compressed sensing problem. Specifically, it returns y = A*x (mode = 1) or y = A *x (mode = 2), where A is an mxn matrix given by A = [Phi - Phi], and Phi = P*H*Q, where P,Q are random permutation matrices, and H is a fast Hadamard/Fourier operator.

使用基于LDA算法的人脸识别程序，附有相应的论文(LDA algorithm based on the use of face recognition procedure, with the corresponding papers)

Matlab自学教程帮助使用者理解各种指令和功能，加上算法实例的应用，是使用者更好的理解和掌握Matlab常用指令和功能，为以后的学习打下一个良好的基础。(Matlab self-study tutorial helps users understand various instructions and functions, plus the application of algorithm examples, it is better for users to understand and master the common instructions and functions of Matlab, and lay a good foundation for future learning.)

说明：  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.)

一维电阻率模拟Matlab源代码，很好的Matlab滤波源代码资料(a Matlab program to model 1D complex resistivity effects in electrical and electromagnetic surveys)

说明：  信号SG平滑滤波Matlab程序仿真，简单实用，对信号的前期处理很有用(SG signal smoothing filter Matlab simulation program, simple and practical, pre-treatment of the useful signal)

在分析最小均方自适应滤波器(LMSAF)均方误差(MSE)的收敛性时，文献常用统计自相关矩阵代替瞬时自相关矩阵以简化分析，由此得出的收敛条件比较粗糙。本程序指出：不相关高斯输入情况下，无需如上简化，可依据高斯阶矩因式分解定理得到确切的MSE收敛条件，相应的失调表式能更准确地预报失调(In the analysis of LMS adaptive filter (LMSAF) the mean square error (MSE) convergence, the literature commonly used statistical correlation matrix instead of the instantaneous correlation matrix to simplify the analysis, it follows that the convergence conditions are relatively rough. This procedure pointed out: not related to the Gaussian input case, no simplification above may be based on the Gaussian moment factoring theorem to the exact order of MSE convergence conditions, the corresponding offset table style to a more accurate prediction of disorder)