MATLAB-Huffman-GUI-design

综合使用多种方法使模糊的人体骨架变清晰，空间图像域的增强(The integrated use of a variety of ways to obscure a clear change in human skeleton)

小球弹跳仿真。重力一定。初始位置一定。三维动画仿真(Bouncing ball simulation. Gravity must. Some initial position. Three-dimensional animated simulation)

最小二乘支持向量机，LS_SVM.m为主函数，normalization.m为归一化函数，release.m为反归一化函数。(Least squares support vector machine, LS_SVM.m is the main function, normalization.m is the normalization function, release.m is the normalization function.)

单机无穷大系统仿真。电压恒定，励磁稀疏改变(Machine infinite system simulation. Constant voltage excitation sparse change)

Numerical analysis Numerical Integration Toolbox MATLAB Toolbox for 1-D, 2-D, and n-D Numerical Integration

应用KL变换的人脸识别MATLAB实现,人脸识别可以借鉴(K_L decompsition for face recognition)

局部离群点检测算法，matlab代码实现(local outlier detection)

说明：  相关向量机（Relevance Vector Machine，简称RVM）是Micnacl E.Tipping于2000年提出的一种与SVM（Support Vector Machine）类似的稀疏概率模型，是一种新的监督学习方法。 它的训练是在贝叶斯框架下进行的，在先验参数的结构下基于主动相关决策理论（automatic relevance determination，简称ARD）来移除不相关的点，从而获得稀疏化的模型。在样本数据的迭代学习过程中，大部分参数的后验分布趋于零，与预测值无关，那些非零参数对应的点被称作相关向量（Relevance Vectors），体现了数据中最核心的特征。同支持向量机相比，相关向量机最大的优点就是极大地减少了核函数的计算量，并且也克服了所选核函数必须满足Mercer条件的缺点。(Relevance Vector Machine (RVM) is a sparse probability model similar to SVM (Support Vector Machine) proposed by Micnacl E. Tipping in 2000. It is a new supervised learning method. Its training is carried out under the Bayesian framework. Under the structure of prior parameters, it is based on Automatic Relevance Determination (ARD) to remove the irrelevant points, so as to obtain the sparse model. In the iterative learning process of sample data, the posterior distribution of most parameters tends to zero, which is independent of the predicted value. The points corresponding to non-zero parameters are called Relevance Vectors, which represent the most core features of the data. Compared with support vector machine, the biggest advantage of correlation vector machine is that it greatly reduces the computation amount of kernel function, and also overcomes the shortcoming that the selected kernel function must meet Mercer's condition.)

对CDMA通信系统进行matlab仿真，包括Viterbi编码（卷积编码），交织，扩频，调制，解调，抽样判决，解偏置,码型转换，解交织等源代码，给出了误码率曲线。(Matlab on the CDMA communication system simulation, including the Viterbi coding (convolutional coding), interleaving, spreading, modulation, demodulation, sampling decisions, solve bias, format conversion, such as source code deinterleave given bit error rate curve.)

这是我自己编写的一个改进的经验模态分解EEMD的源码，希望大家能用上(This is what I have written an improved empirical mode decomposition EEMD source code, I hope everyone can be on)