nncontrol

说明：  噪声子空间法 进行波达估计 算法较复杂 不过效果明显(Noise subspace method-of-arrival estimation algorithm significantly more complex, however the effect of)

Región Alcanzable para reactor cstr y pfr

雷达信号处理的matlab程序及各种滤波器设计(Radar signal processing matlab program and a variety of filter design)

相控阵天线中,对各个子阵的幅度加权不同达到降低旁瓣的目的，本程序是子阵加权（taylor）程序(The phased array antenna, for each sub array amplitude weighting of different reduce sidelobe purpose, this procedure is the subarray weighting (Taylor) program)

说明：  结合PCA的尺度不变特征变换(SIFT)算法源代码，可用于图像目标检测和识别(Combined with PCA scale invariant feature transform (SIFT) algorithm source code, can be used for image target detection and recognition)

Matlab交互式多模型UKF和EKF滤波程序（附说明文档） (Matlab interacting multiple model UKF and EKF filtering procedures (with documentation))

dijkstra算法的matlab实现，最短路问题的一种解法。(dijkstra algorithm Matlab implementation, the shortest path to a solution of the problem.)

说明：  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.

自编的遗传算法代码实际例子，比较简单，请多指教。(Practical examples of self genetic algorithm code, relatively simple, please enlighten.)

因子分析是指研究从变量群中提取共性因子的统计技术。最早由英国心理学家C.E.斯皮尔曼提出。因子分析可在许多变量中找出隐藏的具有代表性的因子。将相同本质的变量归入一个因子，可减少变量的数目，还可检验变量间关系的假设。(Factor analysis is the study of common factors extracted from the variable group statistical techniques. First proposed by British psychologist CE Spearman. Factor analysis can identify a representative factor to hide many variables. Will be essentially the same variables into one factor, can reduce the number of variables, but also test the hypothesis that the relationship between variables.)