SimAlamouti

压缩感知重构算法的功能代码 内附功能函数的详细说明(Compressed sensing reconstruction algorithm of the function code included a detailed description of performance function)

这是一个非常完整并且正确的软件，里面dmc的所有有关程序，希望能够帮助到别人。(this is very important program，hope that it can help u guys)

直流电机的起动，制动，调速。其中含有各个部分的matlab仿真模型。(DC motor starting, braking, speed. Which contains various parts of matlab simulation model.)

吴恩达教授有关深度学习浅显易懂的算法介绍，包括基础算法和示例。(Deep learning algorithms introduction by Andrew Ng.)

说明：   高阶谱工具箱 Version 2.0.3 (R12 compliant) 27 Dec 2(Higher-order spectrum Toolbox Version 2.0.3 (R12 compliant) 27 Dec 2)

Nelder And MEad Search Method

有限差分。超松弛迭代法相关程序和资料 有限差分。超松弛迭代法相关程序和资料(Finite difference. Super relaxation iteration method relevant procedures and material )

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.)

使用K-MEANS算法进行图像的分割，并且有详细的语句注释(K-MEANS algorithm using image segmentation, and a detailed statement notes)

matlab编写结构计算振型分解法，能求解多自由度问题，自动绘出振型(the preparation of structural calculations matlab vibration mode decomposition method to solve the problem of multi-degree of freedom, automatic mapping mode shape)