pathfollowing_curve

AR模型参数BURG算法估计的功能函数及源代码(BURG AR model parameter estimation algorithm performance function and source code)

基于小波变换的数字水印算法matlab代码，滤波求和方式实现宽带波束形成，包括轨道机动仿真、初轨计算。( Based on wavelet transform digital watermarking algorithm matlab code, Filtering summation way broadband beamforming, Including orbital maneuvering simulation, initial orbit calculation.)

说明：  DCDC全桥斩波的电路仿真，使用传统的PID算法(DCDC full bridge chopper circuit simulation, using the traditional PID algorithm)

Dear Sir, I have upload some source codes of image processing & digital signal processing performed on matlab platform to avail the membership from you. Thank You.

说明：  OFDM系统点对点收发的误码率分析,采用瑞丽信道，可以对收发帧数等进行修改(BER for OFDM system)

说明：  数据预测之BP神经网络具体应用以及matlab代码(Application of BP neural network in data prediction and matlab code)

MATLAB 的一写小总结，传上来供大家方便。欢迎下载。(MATLAB Writing a small summary of the 1, Chuan-up for the convenience of everyone. Welcome to download.)

small signal analysis of power system matlab toolbox

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.)

用MATLAB编写的加密代码 先将源文件翻译成ASCII码 在对其进行加密(Encrypted code written with MATLAB source file first translated into ASCII code in its encrypted)