EFG-solver

This program simulates plant identification least mean square (NLMS) alogrithm reference: 《LMS算法的频域快速实现》(This program simulates plant identification least mean square (NLMS) alogrithm reference: LMS algorithm for rapid realization of the frequency domain )

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.)

这是在张正友摄像机标定的基础上对其算法进行改进，实现投影仪算法的一个简单程序(This is at Zhengyou Zhang' s camera calibration algorithm based on its improved algorithm implementation projector a simple procedure)

Interactive smoothing for time-series

十大经典人工智能算法之一——K最近邻Matlab实现(One of the top ten classical artificial intelligence algorithms- K nearest neighbor Matlab implementation)

实现一定tari和采样频率下的PIE编码，输入一定长度的随机数字信号，输出经过PIE编码的方波序列(PIE coding to achieve certain tari and sampling frequency, random length digital signal input and output through the square wave sequence encoding PIE)

清华大学数学实验之插值与拟合幻灯片与MAT源码(Tsinghua University, Experimental Math slides of interpolation and fitting with the MAT-source)

OPNET源码，将CRC检验应用于新型网络体系结构SUPA的分帧。(it s a OPNET simulation,which is about SUPANET, a next generation network architecture. CRC in this circumstance is used for EPF frame divided)

数字图象处理系统，使用MATLAB的GUI模块，可实现图象的直方图均衡、灰度化、二值化、缩放、边缘检测、增加噪声、图像变换、去噪等功能。使用时请将fig文件和m文件和图像放在一个文件夹内(photo process system,use matlab)

说明：  此仿真实现了单位功率因数的有源逆变，也可功率因数可调。(The simulation of active power factor of the unit, also can be inverter power factor can be adjusted. )