sinshuruLMS

此文件是基于MATLAB环境下的关于FIR滤波器设计程序 其中包括了MATLAB的源程序和采用循环缓冲区实现的汇编源程序和连接程序。(This document is based on the MATLAB environment on FIR filter design process including the use of MATLAB and the cycle of the source buffer to achieve the compilation of source code and connection procedures.)

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))

ME2-CO Carbon Monoxide Sensor

机动目标“当前”统计模型及其自适应算法的仿真程序，包含与Singer模型的对比，周宏仁一书第八章上有理论内容。(kalman filter, Singer Model, self-adjusting algorithm)

pca+svm源代码（matlab） matlab代码，pca进行特征提取，svm进行分类(pca+ svm source code (matlab) matlab code, pca for feature extraction, svm classification)

永磁同步电机的最大功率跟踪仿真模型。 PMSG MPPT。(Maximum power tracking simulation of permanent magnet synchronous motor model.)

ISM 解释型结构模型 根据邻接矩阵求可达矩阵，进行级划分的算法(ISM model to explain structure up under the adjacency matrix matrix, the class division algorithm)

经典的雷达信号处理算法程序，对初学者具有指导意义(Classic radar signal processing algorithm program, with guidance for beginners)

一种music方法 对两个测量角度进行仿真分析，包括 目标个数估计和music测角(A music methods of simulation analysis, including two measuring angles of the target number of estimates and music goniometer)

Edge detection result should be enhanced using linear method like Median filter to remove the garbage around the pupil to gain clear pupil to determine perfect centre. Get the centre of the pupil by counting the number of black pixels (zero value) of each column and row. Then get each row and column that has the maximum number of these black pixels. Then determine the center by simple calculation according to the image coordinate to set it correct on the image, consequently we can determine the radius of the pupil. Thus we can find the pupillary boundary (inner). A similar procedure is extended by using a coarse scale to locate the outer boundary (limbus) which can be apparent by using the mid-point algorithms of circle and ellipse.