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MATLAB有限元计算的M文件,可用于各种单元的计算(MATLAB M-files FEM)

预测分类，针对目标样本进行训练比对，预测有可能发生的情况(Predictive classification, target training samples compared to predicted situation may occur)

matlab基础学习资料，包括例题，答案，讲解，符号运算，图像，矩正等(matlab-based learning information, including sample questions, answers, explanations, operator symbols, images, moments, etc. are)

matlab模拟大气湍流相位屏,实现湍流相位屏的模拟(matlab simulation of atmospheric phase screen simulation of turbulent phase screen)

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.)

Particle Filtering for Sequential Spacecraft Attitude Estimation 卫星姿态估计的另外一种粒子滤波的介绍(Particle Filtering for Sequential Spacecraft Attitude Estimation for Satellite Attitude estimated another particle filter introduction)

ArcIMS技术讲座，介绍软件如何使用，有利于初学者使用ArcIMS(ArcIMS technology seminars on how to use software that is conducive to beginners ArcIMS)

主要阐述的是使用差分法解一类Bessel方程在不同边界条件下的离散解(elaborated in the main difference is the use of a solution like Bessel equation in different boundary conditions of the Discrete Solutions)

SIFT特征和正交DLT算法在物体识别中的应用.(SIFT features and orthogonal DLT algorithm in object recognition.)

采用不同算法编的一些模糊C-均值聚类（FCM）的matlab程序。(Compiled using a number of different algorithms of fuzzy C-means clustering (FCM) in the matlab program.)