6.1.10SimulinkTDSDModel

basics of matlab to start with

一维，ＦＤＴＤ，ｍｕｒ，ｍａｔｌａｂ语言。(One-dimensional, FDTD, mur, matlab language.)

主要是关于图形应用和图形处理的一些程序,还有关于界面设计的一些内容(mainly about the apllication of graphics)

Fiber modes Written by JM DeFreitas, QinetiQ Ltd, Winfrith Technology

dIVISIVE CLUSTER ALGORITHM

说明：  MIMO信道初始化的MATLAB仿真源程序(intimate mimo channel source)

产生右图所示图像f1(m,n)，其中图像大小为256×256，中间亮条为128 ×32，暗处=0，亮处=100。对其进行FFT： ① 同屏显示原图f1(m,n)和FFT(f1)的幅度谱图； ② 若令f2(m,n)=（-1）m+n f1(m,n)，重复以上过程，比较二者幅度 谱的异同，简述理由； ③ 若将f2(m,n)顺时针旋转90 度得到f3(m,n)，试显示FFT(f3)的幅 度谱，并与FFT(f2)的幅度谱进行比较； ④ 若将f1(m,n) 顺时针旋转90 度得到f4(m,n)，令f5(m,n)=f1(m,n)+f4(m,n)，试显 示FFT(f5)的幅度谱，并指出其与FFT(f1)和FFT(f4)的关系； ⑤ 若令f6(m,n)=f2(m,n)+f3(m,n)，试显示FFT(f6)的幅度谱，并指出其与FFT(f2)和 FFT(f3)的关系，比较FFT(f6)和FFT(f5)的幅度谱。(Generating an image f1 (m, n) shown in the figure, wherein the image size is 256 256, the intermediate light bar 128 32 0 = dark, bright Department 100. Its FFT: ① screen display picture f1 (m, n) and the FFT (f1) of the amplitude spectrum ② If so f2 (m, n) = (-1) m+n f1 (m, n), repeat The above process, comparing the amplitude spectrum of the similarities and differences between the two, brief reasons ③ If f2 (m, n) 90 degrees clockwise to get f3 (m, n), try to display FFT (f3) the amplitude spectrum and with the FFT (f2) comparing the amplitude spectrum ④ If f1 (m, n) obtained by 90 degrees clockwise f4 (m, n), so f5 (m, n) = f1 (m, n)+f4 (m, n ), try to display FFT (f5) amplitude spectrum, and pointed out its relationship with the FFT (f1) and FFT (f4) of ⑤ If so f6 (m, n) = f2 (m, n)+f3 (m, n) and try to display the FFT (f6) amplitude spectrum, and pointed out its relationship with the FFT (f2) and FFT (f3), comparing FFT (f6) and FFT (f5) amplitude spectrum.)

说明：  滑动DFT实现短时傅里叶变换的matlab代码，包括正变换和逆变换，可极大提高时频分析的计算效率(Sliding DFT to realize short-time Fourier transform matlab code, including positive and inverse transforms, can greatly improve the efficiency of time-frequency analysis.)

根据输入的相应数据，绘制数据的自功率谱幅值曲线图(According to the corresponding input data, drawing data from the power spectrum amplitude curve)

稀疏非负矩阵分解，稀疏非负矩阵分解（SNMF）在线形稀疏编码理论的基础上将大量数据分解成正稀疏分量的一种算法(SNMF，Sparse non-negative matrix factorization)