matlab-help

说明：  有关matlab一简单的试验程序，可以当初步学习时参考使用(On the matlab a simple test procedures, can be a reference to the use of a preliminary study)

基于遗传算法的以最小二乘法为准则条件下的电动汽车与内燃汽车的成本对比(Cost comparison based on genetic algorithm, the least squares method for the guidelines under the conditions of electric vehicles with internal combustion automobile)

检查/剪裁的例子 孤立点检测实例 正交回归的例子 单因数变异数(泊松回归/逻辑回归)的例子 鲁棒回归的例子 特征选择的例子 常见的边坡问题的例子 (Censoring/clipping example Outlier detection example Orthogonal regression example GLM (Poisson regression/logistic regression) example Robust regression example Feature selection example Common slope problem example )

EEg signal classification coding

Long terem eveloultion...LTE-A

人脸识别基于主成分分析（PCA）的matlab实现，附带部分注释。(PCA achieve recognition)

一种基于鲁棒自适应的机器人PD控制，由非线性PD反馈和补偿控制两部分组成。(PD control based on robust adaptive robot controlled by a non-linear PD feedback and compensation of two parts.)

说明：  1-32是：图形应用篇 33-66是：界面设计篇 67-84是：图形处理篇 85-100是：数值分析篇(1-32 : the application of graphics 33-66 : graphics interface design 67-84 : graphics processing 85-100: Numerical Analysis )

应用于永磁同步电机的降阶扩展卡尔曼滤波matlab算法程序，PMSM(Reduced-order extended Kalman filtering procedures, PMSM)

研究表明超高斯分布更加贴近语音信号的实际分布，然而语音信号很难用单一的概率密度 函数准确描述，针对这一情况，提出了一种用超高斯混合模型对语音信号幅度谱建模的新方法，并推导了 基于此模型的幅度谱最小均方误差估的估计式。仿真结果表明：与传统的短时谱估计算法相比，该算法不 仅能够进一步提高增强语音的信噪比，而且可以有效减小增强语音的失真度，提高增强语音的主观感知 质量。 (Recent research indicates that the speech spectral amplitude distributions could be fairly described with super-Gaussian probability density function. However, the complexity of speech signal determines that the distribution statistics ofspeech signal could not be well described by single simple function. Thus a super-Gaussian mixture model for speech spectral amplitude is proposed, and with this model, a minimum mean-square error (MMSE) estimator for speech signals spectral amplitude is derived. The simulation results show that this algorithm based on Gaussian and super-Gaussian speech model could achieve better noise suppression and lower speech distortion as compared with the conventional short-time spectral amplitude estimation algorithm. )