conv2p

沿著軌道運動的紅點，画一个红点让其沿着所画图形开始运动(Along the orbital motion of the red dot)

finite element for waveguide

Genetic algorithm Beecolony PSO

matlab仿真微分方程，分别用欧拉法，改进欧拉法，龙格库塔法，四阶adams显式隐式算法对比精度。(matlab simulation of differential equations, respectively, with Euler, improved Euler method, Runge-Kutta method, fourth-order implicit algorithm adams explicit comparison accuracy.)

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.)

windows环境下的截包代码，学习用，很有价值(windows environment cut package code, learn to use, great value)

说明：  matlab中实现雷达信号处理。 matlab中实现雷达信号处理。(Matlab achieve radar signal processing. Matlab achieve radar signal processing.)

matlab的基本入门教程，可以帮助matlab初学者更加好得掌握这一门编程技巧(matlab basic introductory tutorial to help beginners more matlab too good programming skills to grasp the door)

用于主成分分析学习,非常强大，一学就会，分享了(for Principal component analysis )

模糊聚类分析源程序，包括标准化处理，聚类图，等等(Fuzzy clustering analysis of source code, including the standardization processing, clustering diagram, etc.)