Mean-and-Square

利用小波变换去除阈值信号噪声，功能强大，滤波效果良好(failed to translate)

鲸鱼算法改进优化，结合最小二乘支持向量机，(Whale algorithm optimization)

田口實驗分析程式,將做完田口實驗的實驗數據寫入並可做田口實驗最佳組合的分析,此程式能選擇望大或望小(Taguchi analysis program, will finish the experimental data is written and can do Taguchi Taguchi analysis the best combination, this program can choose to look great or look small)

the file is for light

说明：  扩展卡尔曼滤波的一个原理程序，真实值为常量。(A principle extended Kalman filter procedure, the real value is constant.)

high refractive index metals

说明：  随机共振降噪，用于提取强噪音下的微弱信号(Stochastic resonance noise reduction for weak signal extraction under strong noise)

各种kalman滤波器的设计，小波包分析提取振动信号中的特征频率，最大信噪比的独立分量分析算法。( Various kalman filter design, Wavelet packet analysis to extract vibration signal characteristic frequency, SNR largest independent component analysis algorithm.)

汽车高斯曲面拟合 --- 2程序，以适应到表面二维高斯： 子= A *的进出口（ -（（西为X0）^2/2/sigmax^2 +（艺Y0的）^2/2/sigmay^ 2）。。）+ b的 这些例程是自动在某种意义上说，他们并不需要出发对模型参数的猜测规范。 autoGaussianSurfML（十一，彝，子）适合通过对模型参数的最大似然（最小二乘）。它首先计算了该模型在许多可能的参数值，然后选择最佳质量设置和细化与lsqcurvefit它。 autoGaussianSurfGS（十一，彝，紫）的估计，通过指定数据的贝叶斯生成模型，然后采取通过从模型吉布斯抽样样本后ofthis模型参数。这种(Auto Gaussian Surface fit --- 2 routines to fit a 2D Gaussian to a surface: zi = a*exp(-((xi-x0).^2/2/sigmax^2+ (yi-y0).^2/2/sigmay^2))+ b The routines are automatic in the sense that they do not require the specification of starting guesses for the model parameters. autoGaussianSurfML(xi,yi,zi) fits the model parameters through maximum likelihood(least-squares). It first evaluates the quality of the model at many possible values of the parameters then chooses the best set and refines it with lsqcurvefit. autoGaussianSurfGS(xi,yi,zi) estimates the model parameters by specifying a Bayesian generative model for the data, then taking samples from the posterior ofthis model through Gibbs sampling. This method is insensitive to local minimain posterior and gives meaningful error bars (Bayesian confidence intervals))

Image Enhancement 图像扩展，提高 基于matlab环境(Image Enhancement Image expansion, improve the environment based on matlab)