2D-EMD

系统辨识及其MATLAB仿真,随机序列产生程序(System Identification and MATLAB simulation, random sequence generator)

文中给出了人工鱼群算法的原理和详细描述，并对算法的收敛性能和算法中各参数对收敛性的影响等因素进行了分析 针对组合优化问题，给出了人工鱼群算法在其中的距离、邻域和中心等概念，并给出了算法在组合优化问题中的描述 针对大规模系统的优化问题，给出了基于分解协调思想的人工鱼群算法 给出了人工鱼群算法中常用的一些改进方法(The Analysis and ImProvement of Artifieial Fish-swarm algorithm)

神经网络迭代法，数据量不大，用于图像压缩(Neural network iteration method, the data volume is not large, used for image compression)

MATLAB学习的一些心得以及资料 仅限于私人交流学习(some MATLAB learning experience and information)

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：  matlab文件结合实例，实际的优化例子，很有用的(matlab file with examples, practical optimization example, very useful)

说明：  基于Simulink搭建的燃料电池系统级仿真模型，适合相关matlab专业学生交流学习。(The fuel cell system level simulation model based on Simulink is suitable for the students majoring in MATLAB.)

logistic映射分岔图的四种实现方法(logistic map bifurcation diagram of the four implementations)

说明：  下一代无线城域网—MIMO-OFDM模型，关于ofdm的，有源码(The next generation of wireless MAN-MIMO-OFDM model, on ofdm, there are source)

基于椭圆球面波脉冲组的多进制PPM-UWB系统(M-ary PPM-UWB systems using pswf pulse group)