sensorless_MRAS

说明：  无线传感器网络SEP协议的MATLAB实现(SEP protocol for wireless sensor networks to achieve MATLAB)

很好很强大 (GOOD)

说明：  利用遗传算法优化BP神经网络权值和阈值，然后进行训练，利用训练好的模型进行预估。附实例(The use of genetic algorithm to optimize BP neural network weights and thresholds, and then training, training a good use of forecast models. Attached examples)

局部二进制模式ＬＢＰ，介绍了三种不同的ＬＢＰ算子，用于分析图像的局部纹理特征．(local binary mode LBP, introduced three different LBP operator, Image Analysis for the local texture characteristics.)

最小均方（LMS）自适应算法就是一中已期望响应和滤波输出信号之间误差的均方值最小为准的，依据输入信号在迭代过程中估计梯度矢量，并更新权系数以达到最优的自适应迭代算法。LMS算法是一种梯度最速下降方法，其显著的特点是它的简单性。这算法不需要计算相应的相关函数，也不需要进行矩阵运算。(Minimum mean-square (LMS) adaptive algorithm is that one has to respond to the expectations and filtering the output signal of the mean square error between the value of the minimum-based, based on the input signal is estimated in the iterative process of gradient vector, and to update the weights in order to achieve the most Adaptive iterative algorithm gifted. LMS algorithm is a steepest descent gradient method, and its significant features is its simplicity. This algorithm does not require calculation of the corresponding correlation function, nor the need for matrix calculation.)

三相静止坐标系与两相静止坐标系之间的变换关系(Clarke变换) (Three-phase static coordinate system and two phase transformation relationship between static coordinate system (Clarke transformation）)

关于盲信号处理的毕业论文采用ICA算法，该盲信号处理主要针对语音信号号的混合和分离，用matlab进行仿真实现(About the treatment of the graduation thesis, trimmers by ICA algorithm )

说明：  利用Matlab程序实现蝴蝶混沌效应，该例程形象直观的再现了数值分析有关原理(using Matlab program Chaos Butterfly Effect, the routine visual image of a replay of the numerical analysis of the principle)

机械最优化设计中，无约束条件的最速下降法(Mechanical design optimization, unconstrained conditions steepest descent method)

一维粒子滤波算法先建立状态模型和量测模型，再构造粒子滤波函数，通过统计分析得到估计后的状态变量，就是该算法的基本原理(One-dimensional particle filter algorithm to first establish a state model and measurement model, and then construct the particle filter function to be estimated by statistical analysis after the state variables, that is the basic principle of the algorithm )