FCM-clustering-MATLAB-code

去除图像噪声椒盐噪声高斯噪声实现图像处理(Salt and pepper noise removal of image noise, Gaussian noise, Image Processing)

用matlab环境编写的卡农音乐的源程序，很好听(Canon music source written in Matlab environment, good to hear)

雷达信号处理算法，MTI、MTD、PD相关仿真。(Radar signal processing algorithms, MTI, MTD, PD-related simulation.)

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.)

curvelet denoise matlab code

说明：  MATLAB 的50道入门题目 帮助初学者更快了解和更好的学习MATLAB(Getting Started with MATLAB' s 50 questions to help beginners learn faster and better understanding of MATLAB)

MATLAB高斯噪声生成函数（用于通信）(MATLAB function to generate Gaussian noise (for communication))

matlab仿真经典书籍,包括各种仿真程序，数值计算和各领域的仿真应用，详尽经典(matlab simulation of the classic books, including simulation program, numerical computing and simulation applications in various fields, detailed classic)

说明：  MATLAB开发的文字识别的实例 欢迎下载(MATLAB to develop the character recognition example of welcome to download)

MATLAB code that simulates our proposed Medium Access Control /Power Control protocols (PBOA and PRUA) for ad hoc networks, and compares them with the capacity.