Simple_Adaptive_Control_Example

希尔伯特-黄变换在电力故障中的应用 内含EMD分解 希尔伯特变换算法(Hilbert- Huang transform in power failure in the application)

关于粒子滤波关键技术研究,最新国内外文章(Particle filter on the research of key technologies, the latest article at home and abroad)

基于MATLAB软件的有关雷达杂波的的很多个程序，相信对初学入门者很有帮助 (Based on MATLAB software on the radar clutter of many programs, I believe that is helpful for beginners beginners)

code to solve the gauss equation in laser

说明：  复杂网络BA模型MATLAB 源码，有详细注释(BA model complex networks MATLAB source code, there are detailed notes)

说明：  智能控制,采用了PID,专家整定PID,模糊控制等多种控制策略.(intelligent control, using the PID, experts PID, fuzzy control and other control strategy.)

matlab常用函数命令，各个工具箱中所用到的都包括，还有simulator常用仿真命令，(some important function for matlab ,including all of the tool boxes and simulator)

mathematics with matlab

自己编写的宽带DOA估计中TOPs算法的源代码,希望对大家有帮助。(This is the matlab code of TOPs algorithm in wideband DOA estimation, and I wish to give useful reference for someone. )

这是一个关于稀疏高斯过程的matlab源码，可以用于计算测试输入的高斯预测值。( spgp_pred computes the SPGP predictive distribution for a set of test inputs. You need to supply a set of pseudo-inputs or basis vectors for the approximation, and suitable hyperparameters for the covariance. You can use any method you like for finding the pseudo-inputs , with the simplest obviously being a random subset of the data. It is coded for Gaussian covariance function, but you could very easily alter this. It is also fine to use for high dimensional data sets. spgp_lik is the SPGP (negative) marginal likelihood and gradients with respect to pseudo-inputs and hyperparameters. So you can use this if you wish to try to optimize the positioning of pseudo-inputs and find good hyperparameters, before using spgp_pred . I would recommend initializing the pseudo-inputs on a random subset of the data, and initializing the hyperparameters sensibly. Its current limitations are that 1) it is slow and memory intensive for high dimensional data sets 2) it is heavi)