bp-ga

非常详细的MUSIC谱估计程序，自己写的，毕业设计，保证结果正确且可以运行。有非常详细的注释，每句话都有注解，简明易懂，保证可以看懂并学到知识，并且每一步与MUSIC算法详细的对应和算法解释，不管是学习程序还是学习算法都很有帮助，.m文件中是程序的一部分，全部代码在WORD中，肯定是你见过的最好的代码(MUSIC spectrum estimation very detailed procedures for their own writing, graduation, there are very detailed notes, every word has a comment, simple to understand, to ensure you can read and acquire knowledge, and every step of the MUSIC algorithm and the corresponding detailed and algorithm explanation, whether the learning process or learning algorithms are very helpful)

System will automatically delete the directory of debug and release, so please do not put files on these two directory.

一个比较好的APSO代码，MATLAB程序(A better APSO code, MATLAB program)

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.)

matlab图像处理领域类的一种常用算法。对初学者有很大的帮助(matlab image processing class, a common algorithm. Very helpful for beginners)

通过寻找Z变换矩阵，对给定矩阵进行降相关运算。相关专业的朋友懂的。(By finding the transformation matrix Z, given the lower correlation matrix operations. Relevant professional friends understand.)

利用x(n)=Asin(pi*n/16)+z(n),z(n)为mean=0，var=0.1高斯白噪声，x(n)的SNR为10dB,s(n)=Asin(pi*n/16-5*pi),得出了x(n)和s(n)互相关函数r(n)，以及二者的卷积和.(The utilization for the mean of x (n) = Asin (pi* n/16)+ z (n), z (n) = 0, var = 0.1 Gaussian white noise, x (n) is the SNR as 10dB, s (n) =Asin (pi* n/16-5* pi), draw the x (n) and s (n) the cross-correlation function r (n), as well as the convolution of the two.)

对给定语料估计其基音周期。 要求用MATLAB或C语言实现有关基音检测算法，并给出检测结果。 (For a given corpus to estimate the pitch period. Required to use MATLAB or C language realization of the pitch detection algorithm, and gives test results.)

本程序为一个对流层延迟修正模型的matlab代码，可以较为准确的修正对流层延迟修正(This program is a tropospheric delay correction model matlab code, can provide a more accurate correction tropospheric delay correction)

HFS algorithm for identifying