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MATLAB 数学手册复合版内容详尽 包括矩阵及其基本运算，特征值与二次型数值计算与数据分析 插值、拟合与查表 常微分方程数值解偏微分方程的数值解 符号运算积分变换Taylor级数 概率统计 随机数的产生 随机变量的概率密度计算 随机变量的累积概率值(分布函数值)正整数的频率表 4.6.2 经验累积分布函数图形 最小二乘拟合直线 绘制正态分布概率图形 绘制威布尔(Weibull)概率图形 样本数据的盒图 给当前图形加一条参考线 在当前图形中加入一条多项式曲线 样本的概率图 附加有正态密度曲线的直方图在指定的界线之间画正态密度曲 假设检验 方差分析 foptions函数 非线性规划问题 隶属函数 模糊推理结构FIS 绘图与图形处理 含有基本实例代码 (MATLAB math composite version of the manual includes a detailed matrix and the basic computing, quadratic eigenvalue with numerical analysis and data interpolation, fitting with the look-up table the numerical solution of ordinary differential equations numerical solution of partial differential equations symbols computing integral transforms Taylor class the number of probability and statistics of the generated random number of random variables the probability density of random variable cumulative probability values (distribution function value) positive integer frequency table 4.6.2 graphical experience distribution function least-squares fitting a straight line Normal probability graph drawing Drawing Weibull (Weibull) probability graph Sample data box diagram To add a reference to the current graphics line In the current graph by adding a polynomial curve Additional samples have the probability map is the histogram density of states curve at the specified)

用simulink搭建的2dpsk调制及解调的通信系统(Simulink structures 2dpsk with modulation and demodulation of the communication system)

说明：  多元线性回归的MatLAB代码，在MatLAB7.0运行成功！(Multiple linear regression MatLAB code, MatLAB7.0 runs successfully!)

介绍matlab中字符串、元胞和构架数组的建立、使用和用法(Introduction matlab in the string array of cellular and framework of the establishment, use and usage)

moving object dection with the three dimendional analysis

paper file from the tool box of some matlab code

2*2 mimo-ofdm using awgn channel

雷达对抗原理 单脉冲测角 文档 源代码 matlab编程(matlab )

加权最小二乘迭代求解多参数估值。用于求解平差问题及其他领域优化问题。(The weighted least-squares iterative solution of multi-parameter estimates. Adjustment for solving optimization problems and other problem areas.)

GM8126 Simple IPCAM demo source code