LDPC译码算法的matlab实现

射频方面的技术文档:天线测试手机射频特性测量解决方案及应用(RF technical documents: RF characteristics of mobile phone antenna test measurement solution and application)

matlab版本 图论中的kruskal算法 一般C版本的比较多，这里提供matlab版本的，更简单方便使用 (Matlab code of kruskal algorithm in graph theory)

some lecture about the extend kalman filter algorithm ,which is very useful for the beginner.if you down load it ,it will be of great convenient for you.

This is the Gaussian piramyd i found in matlab page is very useful to image procesing

模糊综合评判方法即将评价目标看成是由多种因素组成的模糊集合（称为因素集u），再设定这些因素所能选取的评审等级，组成评语的模糊集合（称为评判集v），分别求出各单一因素对各个评审等级的归属程度（称为模糊矩阵），然后根据各个因素在评价目标中的权重分配，通过计算（称为模糊矩阵合成），求出评价的定量解值。它是应用模糊变换原理和最大隶属度原则，对各因素作综合评价的。(The fuzzy comprehensive evaluation method is about evaluation goal as a fuzzy set by a variety of factors (called factor set u) set the assessment level of these factors can be selected to form the fuzzy set of reviews (called evaluation set v) were calculated the level of the individual assessment of each single factor attribution the quantitative solution value (called a fuzzy matrix), then the weight distribution according to various factors in the evaluation objectives, by calculating (called fuzzy matrix synthesis), obtained evaluation . It is the application of fuzzy transform principle and the principle of maximum degree of membership for a comprehensive evaluation of various factors.)

matlab练习程序（最大类间方差二值化图像）这里用的方法是《特征提取与图像处理》3.3.4里的。( matlab exercise program (Otsu binary image))

Persian calender mfile 1392 in matlab

对图像进行灰度化，直方图，二值化，边缘检测和阈值分割(Gray image, histogram, edge detection)

垂直泊车仿真模型，采用三段弧式路径规划，能够实现在不同起始点下的垂直泊车(Vertical parking simulation model, using three-stage arc path planning, to achieve vertical departure at different starting points)

CLC;清除所有;关闭所有;％创建一个对象的BiographSRC =[11 1 2 23 4 4 55 6 67 7 89 9 91111 12 13];DST= [23843611576101410891012131213 1414]。体重=[2100300048001500120030039001200 1200240036002100150027001500 1500600 60012001500600300];DG=稀疏（SRC，DST，重量，14,14）;fprintf中（“DG= N"）;DISP（DG）;UG= TRIL（DG+ DG"）;bg=biograph(UG,[],"ShowArrows","off","ShowWeight","on","NodeAutoSize","on","NodeCallback",true,"EdgeCallback",true);H =视图（BG）;％勘定NOE位置集（h.Nodes（1），"位置"，[38128]，“标签”，“西雅图WA"）;集（h.Nodes（2）中，“位置”，[9,86]，"标签"，"帕洛阿尔托CA"）;集（h.Nodes（3）中，“位置”，[35,24]，“标签”，“圣地亚哥CA"）;集（h.Nodes（4），“位置”，[61,73]，“标签”，“盐湖城UT"）;集（h.Nodes（5），“位置”，[94,63]，"标签"，"博尔德CO"）;集（h.Nodes（6），"位置"，[117,9]，“标签”，“休斯顿”）;集（h.Nodes（7），"位置"，[128,70]，"标签"，"凌嘉在NE"）;集（h.Nodes（8），“位置”，[162,99]，“标签”，“香槟IL"）;集（h.Nodes（9），"位置"，[199,94]，“标签”，“宾夕法尼亚州匹兹堡"）;集（h.Nodes（10），"位置"，[199.51,20.893]，"