08

this is matrix converter file with simulink

Codificador de voz a 8 kbps implementado en microblaze.

仅通过动量效应筛选期货品种，从而构建期货多品种对冲策略(M effect for Multi-futures stratege)

OFDM和CDMA的文章，里面附带程序，希望对大家有用！(OFDM and CDMA articles, which incidental procedures, useful for all of us hope!)

主要是关于灰度共生矩阵应用，其中将灰度共生矩阵从0，45，90，135四个方向进行了计算，并对共生矩阵能量、熵、惯性矩、相关4个纹理参数进行了计算，十分有用。(Mainly on the GLCM application, which will GLCM from 0,45,90,135 four directions were calculated, and the co-occurrence matrix of energy, entropy, moment of inertia, related to four texture parameters were calculated, very useful.)

七单元天线阵MUSIC DOA估计： d=1 ， 天线阵元的间距； lma=2， 信号中心波长； 四输入信号； A=[A1,A2,A3,A4]， 得出A矩； 四信号的频率d=[1.3*cos(v1*n) 1*sin(v2*n) 1*sin(v3*n) 1*sin(v4*n)] 构造输入信号矢量 U=A*d 总的输入信号 总输入信号的协方差矩阵 [s,h]=eig(c) 求协方差的特征矢量及特征值 取出与零特征值对应的特征矢量 求协方差矩阵的逆矩阵 应用Music法估计输出 绘出各波达方向图(Seven-element antenna array MUSIC DOA estimates: d = 1, Antenna Array pitch LMA = 2 signal center wavelength four input signals A = [A1, A2, A3, and A4], drawn A moment tetra-frequency of the signal D = [1.3* cos (V1* n) 1* ⁢ sin (v2* n) 1* sin (v3* n) 1* sin (V4* n)] constructed input signal vector U = A* D of the total input signal of the total input signal covariance matrix [S] = EIG (c) seeking covariance feature vector and the feature value removing and corresponding to the zero eigenvalues ​ ​ characterized vector seeking covariance matrix inverse matrix Applications Music estimate output plotted DOA Figure)

matlab教程，包括matlab语言基础，入门知识，非线性规划，二次规划等内容(matlab tutorial, including matlab language base, getting started, nonlinear programming, quadratic programming and other content)

ＡＲＩＭＡ　matlab实现　，　对时间序列进行预测分析(ARIMA matlab realize, prediction of time series analysis)

參考文獻「Rotation invariant non-rigid shape matching in cluttered scenes」and matlab code. 使用Dynamic Programming Shape Context.(「Rotation invariant non-rigid shape matching in cluttered scenes」and matlab code. Using Dynamic Programming Shape Context.)

Texture segmentatioon with em