FCMClust

本程序是使用MATLAB编写的，包括ASK、BPSK、EPSK、FSK、OOK、QPSK等仿真。(this procedure is the use of MATLAB, including ASK, BPSK, EPSK, FSK, OOK, QPSK, and other simulation.)

路径规划算法,采用人工智能方法模仿机器人通过障碍找到目标(route recognition)

it is a rar file containing source codes of matlab

N层多米诺介质的透射率和反射率随这介质厚度变化的matlab程序仿真。(N-tier transmission media Domino and reflection with the media thickness of the matlab program simulation.)

K-means K均值聚类算法，不是用工具箱编的，对随机产生的数据进行聚类。压缩文件包括m函数、包含主程序和子函数的word文档。(K-means clustering algorithm, not with the toolbox series of randomly generated data clustering.M functions including compressed files, containing the main program and subroutines word document.)

霍夫曼编码的具体方法：先按出现的概率大小排队，把两个最小的概率相加，作为新的概率 和剩余的概率重新排队，再把最小的两个概率相加，再重新排队，直到最后变成1。每次相 加时都将“0”和“1”赋与相加的两个概率，读出时由该符号开始一直走到最后的“1”， 将路线上所遇到的“0”和“1”按最低位到最高位的顺序排好，就是该符号的霍夫曼编码。(Specific methods Huffman coding: the probability of emergence of the size press line, the two smallest sum probability, as a new probability and the probability of re-queue the remaining, then the minimum of two probabilities are added, and then re-queue, until finally become one. Each time the sum will be 0 and 1 Fu added two probabilities, when read by the symbol has come to begin the final 1 , the route will encounter a 0 and 1 at the lowest to the highest bit of the right order, that is the symbol of the Huffman coding.)

QPSK modulation in matlab

本文首先对各种通信信号进行了理论分析，在此基础上针对数字调制信号采用了基于决策论方法的调制方式识别算法，并利用MATLAB软件进行了计算机仿真。本文的调制识别算法是基于决策论方法，该方法具有运算量小，识别效果好等优点(Firstly, the various communication signals are analyzed theoretically, on the basis adopted for digital modulation method based on decision theory, modulation recognition algorithm, and using MATLAB software, the computer simulation. This modulation recognition algorithm is based on the decision theory method, which has the computational load, and good recognition results)

利用Kalman Filter进行机动目标跟踪的例子，附有详细的说明文档(use for tracking moving targets example, with detailed documentation)

深度学习matlab工具箱,包括深度deep belief nets,stacked autoencoder,convolutional neural nets等网络。(Matlab/Octave toolbox for deep learning. Includes Deep Belief Nets, Stacked Autoencoders, Convolutional Neural Nets, Convolutional Autoencoders and vanilla Neural Nets. Each method has examples to get you started.)