资源列表
D2D模式选择
- 用MATLAB实现d2d通信中的模式选择(D2D mode seclection MATLAB)
binaryrep
- 用Matlab编整数转8位二进制，8位二进制转整数，小数转32位二进制及32位二进制转小数的方法(Convert integer to 8 bit binary, 8 bit binary to integer, decimal to 32 bit binary and 32 bit binary to decimal in Matlab.)
UKF
- 卡尔曼滤波的matlab应用 ，程序取自黄小平图书第五章例程123(Calman filtering matlab application, the program is from Huang Xiaoping Book fifth Chapter 123 routine.)
MATLAB代码
- 已知坐标点 画随机图 调用voronoi函数(voronoi function ploting stochastic graph)
arraysignalmusicachieve
- music算法的实现和应用 非常经典好用 很实在(Music algorithm implementation)
channel capacity
- 对不同调制方式（包括BPSK,QPSK,16QAM,64QAM）的信道容量的计算仿真实现(Simulation and implementation of channel capacity for different modulation modes.)
jiefangcheng
- 使用高斯-赛德尔迭代法和雅克比迭代法求解线性方程组；使用高斯法和列主元法求解线性方程组。(Using the Gauss - Seidel iterative method, Jacobi iterative method for solving linear equations and using Gauss method and column principal component method to solve linear equations.)
GMMs
- function对数据EM算法进行fit，并对产生的高斯混合模型的最大似然估计进行绘图。输出结构体obj，带有高斯混合模型的参数mu，sigma。(Function carries out fit for data EM algorithm, and draws the maximum likelihood estimation of the Gauss mixture model. The output structure is obj, with the parameter mu and s
FLC4EV_MM(1)
- In automobiles, a start-stop system or stop-start system automatically shuts down and restarts the internal combustion engine to reduce the amount of time the engine spends idling, thereb
da
- 基于码本（codebook）的背景建模的背景差分法+级联基于LBK或haar的adaboost和基于hog的svm分类器+快速hough圆变换进行人头识别+基于区域特征的目标跟踪算法。(编程) AdaBoost是一种增强性机器学习算法，它用于把弱分类器联合成强分类器；SVM本身就是(Background modeling based on codebook (codebook) background difference method + cascade based on LBK or Haa
fa(4)
- 基于码本（codebook）的背景建模的背景差分法+级联基于LBK或haar的adaboost和基于hog的svm分类器+快速hough圆变换进行人头识别+基于区域特征的目标跟踪算法。(编程)(Background modeling based on codebook (codebook) background difference method + cascade based on LBK or Haar AdaBoost and hog based SVM Classifier + fast
gmm(2)
- 基于码本（codebook）的背景建模的背景差分法+级联基于LBK或haar的adaboost和基于hog的svm分类器+快速hough圆变换进行人头识别(Background modeling based on codebook (codebook) background difference method + cascade based on LBK or Haar AdaBoost and hog based SVM Classifier + fast Hough circle trans