BP_Classification

In this demo, I use the EM algorithm with a Rauch-Tung-Striebel smoother and an M step, which I ve recently derived, to train a two-layer perceptron, so as to classify medical data (kindly provided by Steve Roberts and Will Penny from EE, Imperial College). The data and simulations are described in: Nando de Freitas, Mahesan Niranjan and Andrew Gee Nonlinear State Space Estimation with Neural Networks and the EM algorithm After downloading the file, type "tar -xf EMdemo.tar" to uncompress it. This creates the directory EMdemo containing the required m files. Go to this directory, load matlab5 and type "EMtremor". The figures will then show you the simulation results, including ROC curves, likelihood plots, decision boundaries with error bars, etc. WARNING: Do make sure that you monitor the log-likelihood and check that it is increasing. Due to numerical errors, it might show glitches for some data sets. (In this demo, I use the EM algorithm with a Rauch-Tung-Striebel smoother and an M step, which I ve recently derived, to train a two-layer perceptron, so as to classify medical data (kindly provided by Steve Roberts and Will Penny from EE, Imperial College). The data and simulations are described in: Nando de Freitas, Mahesan Niranjan and Andrew Gee Nonlinear State Space Estimation with Neural Networks and the EM algorithm After downloading the file, type "tar-xf EMdemo.tar" to uncompress it. This creates the directory EMdemo containing the required m files. Go to this directory, load matlab5 and type "EMtremor". The figures will then show you the simulation results, including ROC curves, likelihood plots, decision boundaries with error bars, etc. WARNING: Do make sure that you monitor the log-likelihood and check that it is increasing. Due to numerical errors, it might show glitches for some data sets. )

simulink model of the basic function of soft drink machine

运用MATLAB仿真，实现机器人的避障。(Achieving obstacle avoidance for robots)

用共轭梯度法求解x1^2+4*x2^2.精度为0.1(The Conjugate Gradient Method x1 ^ 2+4* x2 ^ 2. Accuracy of 0.1)

说明：  人脸检测，能用于单人和多人脸图的检测识别，效果不错。(Face detection,It can be used in the detection and recognition of single face and multi face images with good effect.)

人工智能中比较经典的c-means算法的实现。在MATLAB中，数据使用矩阵存储比vc中好实现！(Comparison of artificial intelligence in the classic c-means algorithm. In MATLAB, the use of data storage than the vc matrix of the realization of good!)

scilab,开源数值计算方针软件。实现不同信噪比条件下的频域变换仿真程序，可完美兼容matlab。(Scilab, open source software for numerical calculation principle. Than the frequency domain transform simulation program under different signal-to-noise to achieve, can be perfectly compatible with matlab.)

signal detection in mimo ofdm system using qrdmdfe algorithm

说明：  此代码利用高斯牛顿迭代法，对非线性函数进行参数辨识。可以对传递函数通过阶跃响应实验得到的数据进行迭代获得传递函数的参数(The code uses the Gauss-Newton iteration method to identify the parameters of the non-linear function. The parameters of the transfer function can be obtained by iterating the data obtained from the step response experiment of the transfer function.)

用于流型学习的算法：局部邻域保持 可以分析任何符合流型分布的数据集，常用语人脸识别(For the flow pattern learning algorithm: the local neighborhood to maintain consistent flow pattern can be analyzed the distribution of any data set, common language recognition)