analogCom2

ASK modulation demo for TIMS software. It is the simple script to simulate ASK modulation

Mitra 的数字信号处理书的matlab仿真程序。(Mitra Digital Signal Processing of matlab simulation program book.)

说明：  灰色预测模型matlab程序标签：灰色模型 gm(1 1) 二次拟合 matlab(Gray prediction model matlab program tags: gray model of gm (1 1) quadratic fit matlab)

grayscale decoding method

MA 在迁移的过程中，动态决定节点是否需要进行数据融合 运算，以进一步降低MA 的能量消耗。(MA in the course of migration, determine the need for data fusion node operators to further reduce the energy consumption of MA.)

图论里面的三边交互算法，matlab编制的(The trilateral exchange simple algorithm)

此程序适合平行二元阵天线，三维的，方向图乘积定理。(This procedure is suitable parallel binary array antenna, three-dimensional, the direction of graph product theorem.)

用卡尔曼滤波器实现目标追踪，利用蒙特卡洛的方法对跟踪滤波器进行仿真分析，次数为1000次 (Kalman filter to achieve target tracking, using the Monte Carlo method of tracking filter simulation analysis, the number is 1000 times)

经典capon算法doa估计, 波达方向估计算法,空间角度分辨率有限,简单有效的算法(capon classicdoa estimation algorithm , simple DOA estimation algorithm, space limited angular resolution)

matlab 关于association rule 的自己写的函数，有3个文件, association.m：h = association(m, i, j) i=>j, m是数据，h是support和confidence，该函数只适用于单个数据 ass_item: h=ass_itset(m, a, b) 同上，但是可用于多个数据（m为数组） assrule: h = assrule(m, threshold1, threshold2) 该函数用于classification， 得到规则，threshold1为要求的support,threshold2为要求的confidence，h 则为符合要求的规则及其support和confidence，前2列为规则，后2列为其support和confidence (matlab on the association rule to write functions, there are 3 files, association.m: h = association (m, i, j) i => j, m is the data, h is the support and confidence, this function applies only to a single Data ass_item: h = ass_itset (m, a, b) it is the same as above, but it can be used for multiple data (m can be matrix) assrule: h = assrule (m, threshold1, threshold2) the function used for classification,get the rules, threshold1 is the require of support, threshold2 is the required of confidence, h is the rules and their support and confidence, the former two columns as a rule, the latter two columns as one of its support and confidence)