MonteCarlo_Copulas

基于FFT的大地电磁信号资料处理MATLAB方法实现(Based on the FFT signal magnetotelluric data processing method MATLAB)

有matlab语言编程求解有关一种热传导方程的数值计算方法(a program which is a version of fem_50 for the time-dependent heat equation, by Jochen Alberty, Carsten Carstensen, Stefan Funken)

This submission contains an interface to a LBFGS-code for unconstrained minimization problems of the form min_{x} f(x) + c*| ilde{x}|, where x are the parameters, f is a scalar valued real function, c is a positive scalar (default value=0), |.| denotes the 1-norm, and ilde{x} is some subset of the parameters x.

心电信号低通滤波器、高通滤波器、带阻滤波器、以及QRS波检测(ECG low pass filter and high pass filters, band stop filter, and the QRS wave detection)

工学硕士论文，基于自适应卡尔曼滤波的捷联惯导非线性对准技术研究, (Engineering master's thesis, based on adaptive Kalman filtering SINS Nonlinear Alignment Technology,)

说明：  相干增强扩散，可用于去噪，去噪的同时可较好的保持边缘特征 (failed to translate)

qpsk modulation ofdm main papr

AdaBoost元算法属于boosting系统融合方法中最流行的一种，说白了就是一种串行训练并且最后加权累加的系统融合方法。 具体的流程是：每一个训练样例都赋予相同的权重，并且权重满足归一化，经过第一个分类器分类之后， 计算第一个分类器的权重alpha值，并且更新每一个训练样例的权重，然后再进行第二个分类器的训练，相同的方法....... 直到错误率为0或者达到指定的训练轮数，其中最后预测的标签计算是各系统*alpha的加权和，然后sign（预测值）。 可以看出，训练流程是串行的，并且训练样例的权重是一直在变化的，分错的样本的权重不断加大，正确的样本的权重不断减小。 AdaBoost元算法是boosting中流行的一种，还有其他的系统融合的方法，比如bagging方法以及随机森林。 对于非均衡样本的处理，一般可以通过欠抽样(undersampling)或者过抽样(oversampling)，欠抽样是削减样本的数目， 过抽样是重复的选取某些样本，最好的方法是两种进行结合的方法。 同时可以通过删除离决策边界比较远的样例。 (AdaBoost boosting systems dollar fusion algorithm is the most popular one, it plainly systems integration approach is a serial train and final weighted cumulative. Specific process is: Each training example is given equal weight, and the weights satisfy normalization, after the first classifiers after Calculating a first classifier weights alpha value for each sample and updates right weight training, and then the second classifier training, the same way ....... 0, or until the specified error rate training rounds, wherein the label is the calculation of the final prediction system* alpha weighted and then sign (predicted value). As can be seen, the training process is serial, and weight training examples is always changing, the right of the wrong sample weight continued to increase, the right to correct sample weight decreasing. AdaBoost algorithm is an element, as well as other methods of boosting popular systems integration, such as bagging and random forest method. For )

hot thermo tools for matlab.

标准粒子群算法求解非线性方程，用MATLAB实现，并出仿真结果(The standard particle swarm algorithm for solving nonlinear equations, using MATLAB to achieve, and the simulation results)