dianliulvbo

说明：  s法提取背景，为实现运动目标检测打下基础 matlab (s extraction of background, to lay the foundation for moving target detection matlab)

matlab实现的基于HMM模型的语音识别系统，很实用！(Matlab achieve the HMM-based speech recognition systems, a very practical!)

利用张量cp分解修复数据，对数据进行插补或预测(Use tensor cp decomposition to repair data, interpolate or predict data)

一个简单的matlab通讯的小程序，希望对大家有帮助了(A simple sort of small procedures in the hope we have helped )

这是对matlab的一点简介。希望会对大家有用。(This is a point matlab profile. Hope will be useful.)

说明：  控制流语句if-else-end，并且用学生成绩举例，创建Hilbert矩阵，n阶魔方矩阵，编写一个M函数文件(Control-flow statements if-else-end, and with student achievement, for example, create a Hilbert matrix, n-order magic square matrix, the preparation of an M function file)

一维分形维数的计算，计盒数，看着好才发上来的(One-dimensional calculation of the fractal dimension, box-counting the number was made up to look good)

功率谱估计及其MATLAB仿真.经典功率谱估计是将数据工作区外的未知数据假设为零,相当于数据加窗。经典功率谱估计方法分为:相关函数法(BT法)、周期图法以及两种改进的周期图估计法即平均周期图法和平滑平均周期图法,其中周期图法应用较多,具有代表性。(The power spectrum estimation and simulation of MATLAB. Classic power spectrum estimation is unknown data in the data outside the workspace is assumed to be zero, equivalent to the data window. Classic power spectrum estimation method is divided into: the correlation function method (BT Act), the periodogram and two improved cycle diagram estimation method the average periodogram and smoothed average periodogram, which the periodogram method used more often, on behalf of sex.)

把HHT和神经网络结合起来，识别出是否故障。对于HHT变换，这里用到的是它的IMF分解，然后用能量理论来判别哪些模组是虚假分量，哪些是是真实分量。对于EMD分解后的谱进行特征提取 ，利用的理论基础就是模糊熵。计算出真实 分量的模糊熵，作为输入层；输出层为两个神经元，为0（故障 ）1（正常 （正常 ）判别该信号是否出现故障。(The combination of HHT and neural network to identify whether the fault. For the HHT transform, here is the use of its IMF decomposition, and then use the energy theory to determine which module is false, which is true component. The theoretical basis for the feature extraction of the spectrum after EMD decomposition is fuzzy entropy. The fuzzy entropy of the real component is calculated, as the input layer, the output layer is two neurons, which is 0 (fault) 1 (normal) to determine whether the signal is faulty.)

Noise Remove Code in Matlab