svm-matlab2

继续上传基于稳态kalman滤波器事例讲解，这里可以不需要考虑观测系统中的噪声。(to upload based on steady-state Kalman filter on the case, it need not consider here Observing System of noise.)

这个有中文注释，看得明白，包括主成分分析、因子分析、贝叶斯分析，BP神经网络的整个训练过程。( The Chinese have a comment, understand it, Including principal component analysis, factor analysis, Bayesian analysis, The entire training process BP neural network.)

说明：  将原始数据导入，并运用lstm模型进行模拟运算，主要是做预测分析。(The original data are imported and simulated with LSTM model, mainly for prediction and analysis.)

卡尔曼滤波器完成多传感器数据融合。对多个机器人的不同传感器数据进行融合估计足球精确位置。(Kalman filter to complete the multi-sensor data fusion. Multiple robots of different sensor data fusion estimation football precise location.)

对于非平稳信号，用emd分解后，进行hibert变换后，输出时频三维图，(Output frequency of the three-dimensional map)

matlab程序实例解析 含有源程序 实例(matlab instance analytic examples contain source code)

不同坐标系下相同测量点之间的四元数转换矩阵求解，可以此来求解坐标系A到坐标系B之间的转换矩阵(Different coordinates between the same measurement points quaternion transformation matrix solution can be used to solve this coordinate system A to coordinate system transformation matrix between B)

通过不同的方式演示混沌系统，产生不同的混沌序列。(Chaotic system is demonstrated in different ways, and different chaotic sequences are generated.)

在读入一个图像时，使用量化矩阵对图像做量化(In reading an image, use images to do quantitative quantization matrix)

有关聚类的一些例子，主要是用人工数据点进行分类(Some examples of the relevant cluster, is mainly used to classify artificial data points)