qianghuazhi5

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))

基于反向学习的PSO，在图像阈值分割中的应用(Reverse learning PSO-based application in image segmentation threshold)

an butterworth lowpass filter

说明：  程序描述了电压为-0.377V的情况下，卡尔曼滤波器的输出。其中“+”为观测值。程序注解写的很清楚很容易看懂。(Procedure describes the voltage of-0.377V, the Kalman filter output. Which+ For the observed values. Notes written procedure is easy to understand very clearly.)

样条插值的Matlab实现,使用第一类和第二类边值条件进行插值，有图形实例(spline interpolation)

一个基于谢尔菲德遗传工具箱开发的求函数y=sin（10*∏*x）/x在区间[1,2]上的最小值的一个matlab程序.(It is a matlab program dealing with the minimum of the function y=sin(10*∏*x)/x,writing with shefield Genetic alogrithm toolbox.)

PCA-SIFT算法中用于训练矩阵的程序(training matrix in PCA-SIFT)

python算法，信号分析，获得信号分量的幅值、频率、初相和衰减因子。(python algorithm, signal analysis, signal components obtained amplitude, frequency, phase and attenuation factor early.)

本程序对于 循环统计量中存在的直扩信号进行检测，效果很好(This procedure for the circulation statistics that exist in DSSS signal detection, the effect of good)

This code applies local histogram equalization on an input image with a view to improve its contrast ratio. The image is read, converted to grayscale and resized with the inbuilt function of MATLAB. The window size may be changed, however, the window shift is as per size of the window. The output is definitely a better contrast image as compared to the input but checkerboard effect is evident.