vfm_plot

This is is matlab m file to calculate am,gm,rms, hm

C#，提供C#和matlab直接的调用，使得C#能够很好的使用matlab提供的各种功能 (C#, Matlab and C# directly to the call, C# can make good use of Matlab for the various functions)

matlab有限元分析与应用，包含了一些电子教程，以及有限元源代码，(Matlab finite element analysis and application, including some e-book tutorials and source code)

说明：  关于径向基函数神经网络、两个典型的反馈神经网络Hopfield网络、Elman网络的简单示例，适合初学者掌握径向基函数网络和反馈网络的神经网络工具箱函数，为全面学习这两类网络打下基础。(The simple examples of radial basis function neural network, two typical feedback neural networks Hopfield network and Elman network are suitable for beginners to master the neural network toolbox functions of radial basis function network and feedback network, which lays a foundation for comprehensive learning of these two types of networks.)

FCM算法是一种基于划分的聚类算法，它的思想就是使得被划分到同一簇的对象之间相似度最大，而不同簇之间的相似度最小。模糊C均值算法是普通C均值算法的改进，普通C均值算法对于数据的划分是硬性的，而FCM则是一种柔性的模糊划分(FCM algorithm is a clustering algorithm based on the division, which makes the idea is to be divided into clusters with the greatest similarity between the object, and the similarity between different cluster minimum. Fuzzy C-means algorithm is an ordinary C-means algorithm, the general C-means algorithm for the data are divided into hard and fast, and FCM is a soft fuzzy partition)

说明：  分布式环境的计算，课件的使用，以及各种资源。。。(The research paper of “Segmentation methods of fruit image based on color difference” is mainly about four segmentation methods in fruit-harvesting robot vision, which respectively are dynamic threshold segmentation method, extended Otsu method, improved Otsu combined with genetic arithmetic and adaptive segmentation method based on LVQ network. It is written in a good structure. )

this is a MPSK mudulation with BER and PSD .

DsimOrder Calculate the Dissimilarity index based on order pattern analysis.Input: two time series Output: Dissimilarity index between inputs permutation entropy

differtial implicit function

说明：  该工具包提供了一个用于通过算法、预训练模型和应用程序来设计和实现深度神经网络的框架。您可以使用卷积神经网络（ConvNet、CNN）和长短期记忆 (LSTM) 网络对图像、时序和文本数据执行分类和回归。应用程序和绘图可帮助您可视化激活值、编辑网络架构和监控训练进度。(The toolbox provides a framework for designing and implementing deep neural networks through algorithms, pre training models and applications. You can use convolutional neural networks (convnet, CNN) and long and short term memory (LSTM) networks to perform classification and regression on image, temporal, and text data. Applications and graphics help you visualize activation values, edit network architecture, and monitor training progress.)