wcdma_simulink

说明：  电缆阻抗求取程序，高频电缆串联阻抗，根据高频中压电缆模型建立，(Cable impedance calculation program)

图像处理权威著作:数字图像处理(MATLAB版) Digital Image Processing Using MATLAB M代码 (Image processing authoritative book: Digital Image Processing (MATLAB version) Digital Image Processing Using MATLABM code)

清华大学的中文版的Matlab基础教程，适合初学者入门用。喜欢的下(Tsinghua University, the Chinese version of the Matlab Basic Course, suitable for beginners to use portal. Like the next)

brain tumor detection

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.)

说明：  实现广义旁瓣消除，作为初学者进行简单使用(Realize generalized sidelobe cancellation)

遗传算法的优化，对系统参数进行最优控制，找出满足要求的最优解。(Genetic algorithm optimization, optimal control system parameters to find the optimal solution to meet the requirements.)

modular multi level converter

IMPLEMENTATION OF A ROBUST CONTROLLER

振动理论中运用单自由度系统的实际例子来列出微分方程并使用ode45进行计算解答(Vibration theory using practical examples to list a single degree of freedom system differential equations and calculations using ode45 answer)