SSA

這是一個類神經網路中倒傳遞類神經網路，應用於圖形識別上，可以把兩個不同分類的點，藉由BP找出他的分割線進行區分(This is a type of neural network back-propagation neural network applied to pattern recognition, it can be classified into two different points, by BP to find his distinction between partition lines)

一个基于MATLAB环境开发的扑克牌识别程序，个人觉得很不错，在此与大家分享一下！(MATLAB-based environment for the development of procedures to identify playing cards, personal feel very good in this to share with you some!)

本压缩包含有Tennessee Eastman Process的matlab仿真，利用TEP可对过程控制技术的算法进行性能评估。(The compressed Tennessee Eastman Process matlab simulation, algorithm performance assessment TEP process control technology.)

this code tells how to do denoising an image

自己编的一些关于图像灰度直方图处理的MATLAB源程序，包括加权距离，累加直方图，欧氏距离，直方图相交法，中心距法共5种方法，可选择适合的选用。(Own some on the image histogram processing MATLAB source code, including the weighted distance, cumulative histogram, Euclidean distance, histogram intersection of law, from the Law Center, five kinds of methods to choose the appropriate selection.)

MATLAB的使用讲解，非常详细，包括各种工具箱的使用和SIMULINK的使用，对初学者很有帮助(The use of MATLAB to explain, in great detail, including the use of the toolbox and SIMULINK use, very helpful for beginners)

光子晶体matlab程序，有图像表示！比较长；可以仔细研究！(Photonic crystals matlab program, have images that!)

介绍如何使用matlab实现Fuzzy Logic算法，著作人：Sivanandam Sumathi and Deepa(Introduction to Fuzzy Logic using MatLab- by Sivanandam Sumathi and Deepa)

用一般的最小二乘方法和SVD—TLS（总体最小二成）方法估计观测数据的ARMA模型的AR参数。(Least squares method and with the general SVD-TLS (Twenty-general minimum) to estimate the ARMA model of observed data AR parameters.)

极限学习机（extreme learning machine）ELM是一种简单易用、有效的单隐层前馈神经网络SLFNs学习算法。2006年由南洋理工大学黄广斌副教授提出。传统的神经网络学习算法（如BP算法）需要人为设置大量的网络训练参数，并且很容易产生局部最优解。极限学习机只需要设置网络的隐层节点个数，在算法执行过程中不需要调整网络的输入权值以及隐元的偏置，并且产生唯一的最优解，因此具有学习速度快且泛化性能好的优点。(Extreme Learning Machine (extreme learning machine) ELM is an easy-to-use and effective single hidden layer feedforward neural network the SLFNs learning algorithm. 2006 by the Nanyang Technological University Associate Professor Huang Guangbin. Traditional neural network learning algorithm (BP) artificial network training parameters, and it is easy to generate a local optimal solution. Extreme Learning Machine network only need to set the number of hidden nodes, the algorithm implementation process does not need to adjust the network input weights and hidden element of bias, and only optimal solution, so the learning speed and generalization good performance advantages.)