rs-encoding

displacement autopilot coding for aircraft using matlab

解决图论中最短路问题的最好方法--“Dijstra算法,”通过解析实例模型,对模型算法进行描述、拓展,并给出了求最短路以及求最短路长的MATLAB程序,此程序具有通用性。(The best way to solve the shortest path problem in graph theory is- "Dijstra algorithm," by parsing instance model, the model describes the algorithm, expand, and gives the shortest and seek seek the shortest length of the MATLAB program, this program has versatility.)

ACF中包含两个m文件，一个是自协方差函数（可单独使用）。另一个是自相关函数计算，其调用autocov函数。(ACF contains two m files, one is self-covariance function (which can be used alone). The other is calculated from the correlation function, which calls autocov function.)

排队论模拟matlab 利用仿真模拟排队情况(Queuing theory simulation matlab simulation queuing situation)

汽车动力性，燃油经济性计算,基于MATLAB计算的，汽车理论相关内容。(Automotive power, fuel economy calculation)

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.)

In this directory, we can find the eleven files. The relationship between file name and the number of program written in the book is shown in as follows.

least square the design of matlab code

histogram of each part from RGB image

别人编写插值与拟合的程序，拿回来一直没有用到，不知道对诸位有没有用(Others prepare interpolation and fitting procedures used have not been back, I do not know of you have no use)