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在matlab中采用灰度变换的方法增强图像的对比度(In matlab using gray transform method to enhance the contrast of images)

Comparison of estimates: Pisarenko method, ESPRIT, MUSIC, AR

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.)

使用Jakes方法产生单径Rayleigh衰落信道 输入多普勒频移， 样值之间的时间间隔以及 输出瑞利样值序列的长度，最后计算 输出Ns长的瑞利样值序列，加入多普勒频移

source code Fourth Order Partial Differential Equations for Noise Removal,

计算声音的旋律，利用了听觉模型和相关函数。(Calculation of the melody of the voice)

hi this is tha face detection source code from asqur

如何获得彩色图像的gamma (the value of gamma )

关于MATLAB的编程和应用，及其在去除噪声中的应用，源程序的编写和修改(On MATLAB programming and applications, and its application in noise removal applications, the preparation and revision of the source code)

关于matlab中simulink模块最详细的使用教程。包括每个模块的生成、设置、布局连线等等。非常详细。(On the use of MATLAB Simulink module in the most detailed tutorial. Including build, Setup, layout of the wiring each module, and so on. Very detailed. )