搜索资源列表
FuctionKey
- 一个matlab mex 文件，可以用来在matlab程序中捕捉用户按下的特殊功能健：F1, ..., F12. 使用时，在你的应用程序的 KeyPressFcn的函数体里，是用wgfcnkey，根据其返回值，判断是否有功能健被按下。-a Matlab mex documents, in Matlab can be used to capture user proceedings of the special features? Kin : F1, ..., F12. When used i
mallat.m
- 小波谱分析mallat算法经典程序 clc clear ％％ 1.正弦波定义 f1=50 ％ 频率1 f2=100 ％ 频率2
普通端射阵天线的matlab程序
- 普通端射阵天线的matlab程序 clear; f=3e10; lamda=(3e8)/f; beta=2.*pi/lamda; n=10; t=0:0.01:2*pi; d=lamda/4; W=beta.*d.*cos(t); z1=((n/2).* W)-n/2*beta*d; z2=((1/2).* W)-1/2*beta*d; F1=sin(z1)./(n.*sin(z2)); K1=abs(F1); polar(t,K1) ;
IM-MOPSO
- 改进的多目标粒子群算法，成功解决了多目标优化的经典问题，比如ZDT,KUR,SCH经典优化问题等，只需要对f1,f2函数修改后就可以应用。-Improved many target particle swarm algorithm, success in solving the multi-objective optimization of the classic problems, such as ZDT, KUR, SCH classic optimization problem, only
F1
- AR谱估计算法的matlab仿真，包括Yule-Walker方法、协方差方法、修正协方差方法和burg递推法等-AR spectral estimation algorithm matlab simulation, including the Yule-Walker method, covariance method, modified covariance method and the recursive law burg
f1
- 这个源代码是小世界网络模型MATLAB仿真源代码。-small-world network
fixed_point_systems
- Fixed-point for functions of several variables -Function fixed_point_systems(x0, N) approximates the solution of a system of nonlinear equations F(x) = (f1(x), f2(x), ..., fn(x)) = 0 rewritten in the fixed-point form x = G(x) = (g1(x), g2(x), ..., gn
ddd
- 试用Newton插值多项式计算f(1.13)的近似值-Trial of Newton interpolation approximation of polynomial computation f1.13
window.m
- This scr ipt calculate the Fourier transform of a Rectangular window of 64 points using an aproximation with a DFT of 1024 points,as well as calculates for differents values of f0 and f1 the module of the frecuency response of the windowed signal.
equ_response1
- equalizer respone for channel F1(Z)=.1Z^2-.25Z^1+1-.25Z^-1+.1Z^-2 for zfl with tap=7,9,15-equalizer respone for channel F1(Z)=.1Z^2-.25Z^1+1-.25Z^-1+.1Z^-2 for zfl with tap=7,9,15
FBG
- FBG反射谱，要用的人会非常需要，需要的人可以看看，很不错的-FBG id1=fopen( lambdaCMT.txt , wt ) fid2=fopen( rhoCMT.txt , wt ) f1=inline( -i.*delta.*y1-k.*y2 , t , lambda , wk , delta , k , y1 , y2 ) f2=inline( -k.*y1+i.*delta.*y2 , t , lambda , wk , delta , k
pisa
- 在计算机上产生一组实验数据，首先产生一段零均值白噪声数据u（n）,令功率为 ，让u(n)通过一个三阶FIR： 得到y(n). .y(n)上加三个实正弦信号f1’=0.1,f2’=0.25,f3’=0.26调整 和正弦信号幅度信噪比大致为10dB,50dB,50dB. (1) 令N=256,描绘xn波形； (2)得出真实功率谱密度 . (3) 利用此实验数据Pisarenko谐波分解法估计该实验数据的正弦频率及幅度。-On the computer to generate a
quansusousuosuanfa
- 函数的作用是执行1/4像素精度的运动估计 f1是参考帧,f2是匹配帧 函数首先对初始图像进行分辨率提高4倍的双三次插值 再进行基于块匹配的全搜索运动估计-Full search block matching based motion estimation
f1-f5
- F1-F5, a test bed for Genetic Algorithm Optimization Problems. This is a standard Test bed used by several authors to test the efficiency of their proposed algorithms.
linear-FM-chirp-signal-generate-
- 切普信号生成，可以改变信号的起始频率和最终频率。-Be able to generate a linear-FM “chirp” signal that sweeps in frequency fromω1 = 2pi*f1 to ω1 = 2pi*f2 as time goes from t = 0 to T2. You can change any of these values.
ipower
- Keyboard-controlled interactive power spectrum demonstrator, useful for teaching and learning about the power spectra of different types of signals and the effect of signal duration and sampling rate. Single keystrokes allow you to select the type of
fhrmck
- This function uses eigenfunction analysis to solve the matrix differential equation m*y (t)+c*y (t)+k*y(t)=f1*cos(w*t)+f2*sin(w*t) with initial conditions of y(0)=y0, y (0)=v0-This function uses eigenfunction analysis to solve the matrix differen
aitkenInterp
- AITKEN S INTERPOLATION Aitken s procedure yields systematically and successively better interpolation polynomials corresponding to successively higher order truncation of Newton s divided difference formula. Given a set of x and correspondi
f1
- 用差分进化算法辨识非线性函数的参数，算法简单，实现容易，比较合适初学者-Differential evolution algorithm for identification of nonlinear function parameters, the algorithm is simple, and easy to implement, suitable for beginners
HSJZ
- function [ H ,S ] = HS( f ) UNTITLED2 Summary of this function goes here Detailed explanation goes here syms x1 x2 f1=diff(f,x1) f2=diff(f,x2) S= [f1 f2] H = [diff(f1,x1) diff(f1,x2) diff(f2,x1) diff(f2,x2)] end s0=sub