PSO算法优化PID参数

完整的高阶谱工具箱和说明文档，包括高阶谱在时延估计，信号检测等多个领域的应用(Complete high-end spectrum of the toolbox and documentation, including higher-order spectra in time-delay estimation, signal detection and other fields of application)

Model Predictive Control Eduardo F. Camacho and Carlos Bordons

本程序采用MATLAB语言对电力系统的各种短路计算进行分析计算，如单相接地短路，两相短路，两相接地短路等。(This procedure using MATLAB language for a variety of short-circuit calculation power system analysis and calculation, such as single-phase ground short circuit, two-phase short-circuit, two-phase ground short circuit.)

介绍电机控制的基本原理，矢量控制方法，永磁同步电机无刷直流电机的设计，矢量控制，弱磁控制原理及方法，以及转矩脉动仿真等等(Introduced the basic principles of motor control, vector control, permanent magnet synchronous motor brushless DC motor design, vector control, weakening control principle and method, and the torque ripple simulation, etc.)

ePAPR hypervisor byte channel device driver.

数值计算基本算法 包括 拉格朗日插值，牛顿迭代 辛普森公式 高斯-雅可比迭代 厄米特插值多项式 最小平方逼近等(Basic algorithm for numerical calculation)

Salam Des toolbox que j’ai les télécharger depuis qlq année titre se traitement de signal ou bient signal processing ok

适当选择辅助变量，使之满足相应条件，参数估计值就可以是无偏一致。估计辅助变量法的计算量与最小二乘法相当，但辨识效果却比最小二乘法好的多。尤其当噪声是有色的，而噪声的模型结构又不好确定时，增广最小二乘法和广义最小二乘法一般都不好直接应用，因为他们需要选用特定的模型结构，而辅助变量法不需要确定噪声的模型结构，因此辅助变量法就显得更为灵活，但辅助变量法不能同时获得噪声模型的参数估计。(Choose appropriate secondary variables, meet the relevant conditions and parameter estimate can be unbiased consistent. Estimated auxiliary variable method calculation and least square method is quite, but the identification effect is much better than the least square method. Especially when the noise is colored, and noise model structure and not sure, augmented the least squares and the generalized least squares method is generally not used directly, because they need to choose specific model structure, and auxiliary variable method does not need to make sure that noise model structure, so the auxiliary variable method is more agile, but not at the same time auxiliary variable method for noise model parameter estimation.)

新息kalman原理MATLAB实现，适合初学者。(a simple improved kalman filter based innovation.)

本代码主要实现非线性环境下的势均衡多目标多伯努利滤波器的ukf实现，能有效地解决杂波环境下的多目标跟踪问题。(This code mainly realize the potential of nonlinear environment balanced multi-objective multi-bonuli filter ukf achieve, can effectively solve the problem of multi-target tracking clutter environments.)