FTT

级联码simulink模型,OFDM系统误码率分析(concatenated code in simulink)

模糊系统的simulink仿真，控制一阶和二阶系统(Simulink fuzzy system simulation, control first-order and second-order system)

Interactive smoothing for your own data, with sliders to control derivative order, smooth width, and scale expansion.

有关于图像的区域处理的MATLAB软件,已经上机运行过,对MATLAB编程非常有用(Area on the image processing MATLAB software has been running on the machine before, is very useful for MATLAB programming)

matlab解决黄金分割法一维无约束最优化问题，(use matlab for golden)

《系统辨识与MATLAB仿真-侯媛彬》源程序(" System Identification and MATLAB simulation- Houyuan Bin" source)

Euler折线法求解微分方程 (Euler line method to solve differential equations)

滤波器设计示例：matlab设计IIR基本示例，matlab设计IIR高级示例，matlab窗函数设计FIR滤波器基本示例。(Filter Design Example: matlab basic sample design of IIR, matlab advanced example of IIR design, matlab window function, the basic design of FIR filter example.)

function dg=gplus(x,y,z,x1,x2,y1,y2,z1,z2,p) G=6.67e-11 t222=myfun(x,y,z,x2,y2,z2) t122=myfun(x,y,z,x1,y2,z2) t212=myfun(x,y,z,x2,y1,z2) t221=myfun(x,y,z,x2,y2,z1) t211=myfun(x,y,z,x2,y1,z1) t121=myfun(x,y,z,x1,y2,z1) t112=myfun(x,y,z,x1,y1,z2) t111=myfun(x,y,z,x1,y1,z1) dg=-G*p*1e6*(t222-t122-t212-t221+t211+t121+t112-t111) 转化为g.u. function y=myfun(x,y,z,xi,eta,zeta) R=sqrt((xi-x).^2+(eta-y).^2+(zeta-z).^2) temp1=(xi-x).*log((eta-y)+R) temp2=(eta-y).*log((xi-x)+R) temp3=(zeta-z).*atan((zeta-z).*R/((xi-x).*(eta-y))) 书中所给公式 temp3=-(zeta-z).*atan((xi-x).*(eta-y)./(zeta-z)./R) 上式变换 y=temp1+temp2+temp3 (function dg = gplus (x, y, z, x1, x2, y1, y2, z1, z2, p) G = 6.67e-11 t222 = myfun (x, y, z, x2, y2, z2) t122 = myfun (x, y, z, x1, y2, z2) t212 = myfun (x, y, z, x2, y1, z2) t221 = myfun (x, y, z, x2, y2, z1) t211 = myfun (x, y, z, x2, y1, z1) t121 = myfun (x, y, z, x1, y2, z1) t112 = myfun (x, y, z, x1, y1, z2) t111 = myfun (x, y, z, x1, y1, z1) dg =-G* p* 1e6* (t222-t122-t212-t221+t211+t121+t112-t111) converted the Gu function y = myfun, (x y, z, xi, eta, zeta) R = sqrt ((xi-x). ^ 2+ (eta-y). ^ 2+ (zeta-z). ^ 2) temp1 = (xi-x).* log ((eta-y)+R) temp2 = (eta-y).* log ((xi-x)+R) temp3 = (zeta-z).* atan ((zeta-z).* R/( (xi-x).* (eta-y))) book given formula Temp3 =- (Zeta-z)* ATAN ((Xi-X)* (ETA-y)/(Zeta- Z)/R) the above formula transform Y = temp1+temp2+temp3 )

基于matlab的共轭梯度法,基于这种算法可以求解矩阵的解，以及相应的误差(base on matlab)