xianzai

Dijkstra最短路算法通用Matlab程序(Dijkstra)

文档里是基于matlab的卷积码编码，和维特比译码的程序。(Documentation is based on matlab convolution coding, and Viterbi decoding procedures.)

this function is based on evolutionary algorithm for finding the optimal solution for multiple objective i.e. pareto front for the objectives.

完美的OFDM系统的MATLAB仿真程序，希望对研究OFDM的同志有所帮助(Perfect simulation program MATLAB OFDM system, in the hope of OFDM help comrades)

matlab基础教程终结 欢迎收藏 遇到问题 可以查询 英文官方教材 和help里面的差不多 是一个总结的pdf文件(matlab Essentials Collection welcome the end of a problem you can check the official teaching English and help inside is almost a summary of the pdf file)

说明：  两种不同的假设： H1 ： 0 xn A fn wn ( ) cos(2 ) ( ) = ++ π θ n=1,2,…,N，f0 为规一化频率 H0 ： xn wn () () = n=1,2,…,N 其中 w[n]是均值为 0，方差为 2 σ n 的高斯白噪声，A 已知，样本间相互 独立，信号与噪声相互独立; 相位θ 是随机变量，它服从均匀分布 1 0 2 ( ) 20 p θ π θ π ?? ≤ ≤ = ??? 其它 1）改变输入信噪比（改变 A 或噪声方差均可），给定虚警概率，画出 输入信噪比与检测概率之间的理论曲线。(注意：理论检测曲线与样本 数有关) 2）改变样本数，用 Monte-Carlo 实验方法得出 PF＝0.001 时输入信噪比 与检测概率之间关系曲线（至少三条），并得出结论。 3）改变 M-C 实验次数，样本数不变，用 Monte-Carlo 实验方法得出 PF ＝0.001 时输入信噪比与检测概率之间关系曲线（至少三条），并得出 结论(Draw the theoretical curve between input SNR and detection probability)

matlab 实用程序，非常不错，内容丰富，适合广大初学者(Matlab practical procedures, very good, rich in content, suitable for the majority of beginners)

正态函数的正查反查，可以自己设置标准差与平均值 (Normal function is to check the anti-investigation, can set the standard deviation and mean)

经典统计学 概率论基础,是学习MATLAB的经典手册(All of Statistics)

最小均方（LMS）自适应算法就是一中已期望响应和滤波输出信号之间误差的均方值最小为准的，依据输入信号在迭代过程中估计梯度矢量，并更新权系数以达到最优的自适应迭代算法。LMS算法是一种梯度最速下降方法，其显著的特点是它的简单性。这算法不需要计算相应的相关函数，也不需要进行矩阵运算。(Minimum mean-square (LMS) adaptive algorithm is that one has to respond to the expectations and filtering the output signal of the mean square error between the value of the minimum-based, based on the input signal is estimated in the iterative process of gradient vector, and to update the weights in order to achieve the most Adaptive iterative algorithm gifted. LMS algorithm is a steepest descent gradient method, and its significant features is its simplicity. This algorithm does not require calculation of the corresponding correlation function, nor the need for matrix calculation.)