全面的基于单尺度、多尺度、原始的Retinex算法测试源程序

三级倒立摆的非线性部分采用S函数实现，此为S函数实现的源代码(The nonlinear part of the triple inverted pendulum using S functions to achieve, this is the S function, the source code)

数值分析及其MATLAB实现,包括各种典型的算法(Numerical analysis and MATLAB implementation, including a typical algorithm)

说明：  图像灰度变换、图像的锐化、⑴直方图均衡化（histogram equalization），⑵直方图匹配（histogram matching），⑶邻域平均（neighborhood averaging），⑷局域增强（local enhancement）， ⑸中值滤波（median filtering）。源码(Image gray-scale transformation, image sharpening, ⑴ histogram equalization (histogram equalization), ⑵ histogram matching (histogram matching), ⑶ average neighborhood (neighborhood averaging), ⑷ enhanced local (local enhancement), ⑸ Value filtering (median filtering). Source)

说明：  MIMO信道仿真所需的一些小子程序集合，覆盖面比较多(MIMO channel simulation procedures needed for the collection of some kid, more coverage)

JSON library SimpleJSON

实现图像边缘的傅里叶描述子，可用于边缘检测，形状分析。(Matlab achieve image edge of the Fourier descriptors, can be used for edge detection, shape analysis.)

多目标多学科优化，目标解析分流法ATC的简单例子(Multi Objective, Multi Disciplinary, Analytical Target Cascading (ATC) Demo)

作为类脑计算领域的一个重要研究成果，深度卷积神经网络已经广泛应用到计算机视觉、自然语言处理、信息检索、语音识别、语义理解等多个领域，在工业界和学术界掀起了神经网络研究的浪潮，促进了人工智能的发展。卷积神经网络直接以原始数据作为输入，从大量训练数据中自动学习特征的表示。(As the important research achievement, deep convolutional neural networks have been widely applied to various fields such as computer vision, natural language processing, information retrieval, speech recognition, semantic understanding, and have attracted a wave of neural networks research from both academia and industry and have contributed to the development of artificial intelligence.)

调试通过可以使用，matlab程序运行时导入数据文件作为输入参数，本程序的性能已经达到较高水平，是一种双隐层反向传播神经网络，各种资源分配算法实现，插值与拟合的matlab实现。

Level Set Evolution Without Re-initialization一文的matlab实现(Level Set Evolution Without Re-initialization of the matlab realize one text)