kalman_filter

GM(1,1)模型1-4 1：GM(1,1)模拟模型，在matlab中的输入方法为gm1（x），x指要模拟的序列。 2：GM(1,1)预测模型，在matlab中的输入方法为gm2（x，K），x指要模拟的序列，K指从以后序列第一个数据算起的第k个待预测数据。 3：GM(1,1)群模拟模型，在matlab中的输入方法为gm3（x），x指要模拟的序列。 4：GM(1,1)群预测模型，在matlab中的输入方法为gm4（x，K），x指要模拟的序列，K指从以后序列第一个数据算起的第k个待预测数据。 gm4对序列趋势比较好的数据预测效果较好，对上下变动的数据，特别是后4个数据趋势跟前面的数据相反的，预测效果很差。 gm2对上下变动的数据，预测效果比gm4好，但对趋势较好的数据，预测精度没有gm4高。 gm3比gm1模拟精度要高。 可以以x=[1 3 5 7 9 11 13 15]进行实验。x输入默认行向量。 所有程序在matlab6.0上调试通过。(GM (1,1) 1-4 1 : GM (1,1) simulation model Matlab in the input method for gm1 (x), x entail simulation sequence. 2 : GM (1,1) model, in the Matlab input method for gm2 (x, K), x entail simulated sequence, from the K refers to the first series after a run of data k pending forecast data. 3 : GM (1,1)- simulation model, in the Matlab input method for gm3 (x), x entail simulation sequence. 4 : GM (1,1)- forecasting model, in the Matlab input method for gm4 (x, K), x entail simulated sequence, from the K refers to the first series after a run of data k pending forecast data. Gm4 right sequence relatively good trend data predicted better results, the next change in the data, especially after four data with the previous trend data contrary, predict poor. Gm2 next to the change in forecast resu)

Linear Regression with outlier data

说明：  噪声子空间法 进行波达估计 算法较复杂 不过效果明显(Noise subspace method-of-arrival estimation algorithm significantly more complex, however the effect of)

Hilbert 变换测试 适合新手对Hilbert变换的理解(Hilbert Transformation)

ARMASA 代码工具箱，可以方便地计算信号的AR/ARMA等系数，应用效果较好( DEMO_ARMASA demonstration of some ARMASA toolbox features DEMO_ARMASA is a program script that can be invoked from the command prompt to perform a signal analysis experiment, showing general use of several main ARMASA functions.)

基于阵列信号处理的波达方向估计MVDR算法实现代码(MVDR DOA estimation algorithm code fo linear array signal processing)

完成了PLL锁相环路的产生和控制，其中输入为30kHz，输出为100kHz。(complete the PLL s function,convenent to produce and control,and the frequency of input source is 30kHz,the output is 100kHz)

说明：  摘要地层控制分析与设计问题 无人机（UAV）群系统实现时间。 研究了不同的地层。达到预定时间- 无人机的编队、编队协议各不相同。 首先是群系统，无人机的速度可能不同 当到达编队时。然后，基于共识的方法 用于处理时变信息的形成控制 无人机群系统的问题。必要和充分 无人机群系统实现时变的条件 提出了构造方案。(Abstract-formation control analysis and design problems for unmanned aerial vehicle (UAV) swarm systems to achieve time. varying formations are investigated. To achieve predefined time- varying formations, formation protocols are presented for UAV swarm systems first, where the velocities of UAVS can be different when achieving formations. Then, consensus-based approaches are applied to deal with the time-varyin formation control problems for UAV swarm systems. Necessary and sufficient conditions for UAV swarm systems to achieve time-varying formations are proposed.)

将2D图转为3D图的matlab软件，先要用我设计的VB软件将2D图转为数据，我已经上传了。(Figure 2D map into 3D software)

Electrical machines and drives - Ned Mohan