ganzhiji

说明：  卡尔曼滤波简单例程，一维情况。An Introduction to Kalman Filter中的例子。(Kalman filter is simple routines, one-dimensional situation. An Introduction to Kalman Filter in the example.)

实现Po计算电磁散射单站计算，对于一般的目标可进行简单的计算。(it can be used to calculate the monostatic RCS of the object in matlab)

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.)

ali path source of metronic

教你如何做热图（heatmap），可以显示图像的百分比。(A mathod to tell you how to make a heatmap.)

基于MATLAB开发的PID控制程序，含有详细说明温习，初学者可以参考学习。(MATLAB-based development of the PID control program, with detailed study, beginners can refer to learn.)

MATLAB比较常用的例子，这里举了100个各种方面的例子，自己总结的，这是目录！(Commonly used MATLAB examples cited here, 100 examples of the various aspects of their summing up, which is the directory!)

说明：  euler格式前进、后退和改进的格式，并在一个程序中(euler)

用Matlab绘制股市图形范例，含具体步骤说明(draw figure of stock market with Matlab)

method of false position with Aitken s D2-method