ggphscsf

转载资料， 从文字件1到2，双行。非常有趣，值得一试。(To read line from file1.txt and write (double space) to file2.txt)

说明：  以Newmark法求解受移动载荷作用的梁振动问题(Moving load problem using Newmark in Matlab)

频率采样法：使所设计的FIR数字滤波器的频率特性在某些离散频率点上的值准确地等于所需滤波器在这些频率点处的值，在其他频率处的特性则有较好的逼近。 (Frequency sampling method：Make the FIR digital filters designed by the frequency characteristic in some discrete frequency is equal to the value accurately in these frequency required filter in value, the characteristics of the other frequency place there is a better approximation. )

MUSIC程序，用于DOA估计时频估计的程序，MATLAB标准语言，(MUSIC procedures for the DOA estimates of the frequency estimate procedures, standard MATLAB language,)

粒子群网络优化的肩带源代码应用（PSO）(Particle swarm optimization (PSO aglet source code application))

INTERPOLATION OF A SIGNAL

This MATLAB Code plot the aperture efficiency Vs the subtended angle. The user determine the value of n and the code plot and tell what is the angle value that achieves max efficeiency and the value of this efficiency.

psasp和matlab交互仿真接口程序(psasp and matlab interactive simulation interface program)

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.)

遗传算法及其MATLAB实现 含源程序 GA算法及其MATLAB实现 含源程序(MATLAB Genetic Algorithm and Its realize containing source GA algorithm and its realization with MATLAB source)