APmatlab

sobel 边缘检测 是一种对边缘的检测 非常有效 有用的不方可以试试(sobel Edge detection ，it is a kind of edge detection.Very effectively useful not can try)

machine learning 方面有关于Classification fundamentals的资料，语言是python(Classification fundamentals aspects of machine learning have information about language is python)

一列火车要将n节车厢分别送往n个车站车站按1~n的次序编号，火车按照n, n-1,…, 1的编号次序经过车站。假设车厢的编号就是其目的地车站的编号。 (A train to n cars n stations were sent to stations by 1 ~ n the order of numbers, the train in accordance with n, n-1, ..., 1 after the station number sequence. Suppose car number is its destination station number.)

改代码为基于Konhone网络的分类算法，是MATLAB人工智能的经典算法(Change the code based classification algorithm Konhone networks, artificial intelligence is a classical algorithm MATLAB)

single input single output toolbox

采用N=11的标准线阵，进行DOA估计，要求有两个信号。采用MUSIC算法(Standard linear array with N = 11, DOA estimation, requires two signals. Using the MUSIC algorithm)

说明：  该文件包含对AR模型的源程序，并且包含了原始的数据(This file contains the AR model of the source, and contains the original data)

Y.T.Chan在其论文中提出一种具有解析表达式解的非递归双曲线方程组解法，该算法具有计算量小，速度快，且当TDOA参数估计误差服从高斯分布的情况下，定位精度较高。 本程序借鉴Chan论文中提出的算法，基于MATLAB程序，在已知TDOA估计参数的情况下，对信号源位置进行估计。 希望能够对研究 干扰源定位、无源定位的同志提供帮助。(YTChan in his paper presents a solution with the analytical expression for the non-recursive solution of hyperbolic equations, the algorithm has calculated the amount of small, fast, and when the TDOA estimation error of Gaussian distribution in the case, positioning accuracy than high. The papers presented in the program learn from Chan algorithm, MATLAB-based program, known TDOA estimation parameters in the case, the signal source location estimates. Hope to the study of interference location, passive positioning of the comrades to help.)

该代码为基于灰色神经网络的预测算法，里面数据累加作为网络输入(The code is based on the gray neural network prediction algorithm)

此程序描述OFDM系统中多径衰落信道的仿真和实现，包含信道转移矩阵的计算和变换等(This procedure describes the OFDM system simulation and implementation of multipath fading channels, including the calculation and conversion channel transfer matrix, etc.)