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jabberd-2.0s11.tar
- jabber jabberTest.rar - Id: pasvlogin.c,v 1.10 2003/02/16 04:18:47 dpuryear Exp $ * * Just logon n users. Do not send any message traffic (2006-04-03，C-C++,45KB,6次) miranda-im-v0.4src.zip - 基于windows API的即时通讯软件，采用jabber开放协议，可以和msn qq等互通 (2005-06-2
improved_gaborfilter
- Bi-dimensional Gabor filter with DC component compensation This version of the 2D Gabor filter is basically a bi-dimensional Gaussian function centered at origin (0,0) with variance S modulated by a complex sinusoid with polar frequency (F,W) an
cmcm98b
- 98年全国大学生数学建模竞赛B题“水灾巡视问题”，是一个推销员问题，本题有53个点，所有可能性大约为exp(53),目前没有好方法求出精确解，既然求不出精确解，我们使用模拟退火法求出一个较优解,将所有结点编号为1到53,1到53的排列就是系统的结构,结构的变化规则是:从1到53的排列中随机选取一个子排列,将其反转或将其移至另一处,能量E自然是路径总长度。具体算法描述如下：步1： 设定初始温度T，给定一个初始的巡视路线。步2 ：步3 --8循环K次步3：步 4--7循环M次步4：随机选择路线的一段
two_ray_model
- Modelo de dos rayos de Andrea Goldsmith (figura 2.5, según expresión 2.12) f = 0.9 frecuencia en GHz landa = 0.3/f en m R = -1 coeficiente de reflexión en tierra ht = 10 altura del transmisor en m hr = 2 altura del receptor en m Gt
we
- 七单元天线阵DOA估计 clear clc d=1 天线阵元的间距 lma=2 信号中心波长 q1=1*pi/4 q2=1*pi/3 q3=1*pi/6 q4=3*pi/4 四输入信号的方向 A1=[exp(-2*pi*j*d*[0:6]*cos(q1)/lma)] 求阵因子 A2=[exp(-2*pi*j*d*[0:6]*cos(q2)/lma)] A3=[exp(-2*pi*j*d*[0:6]*cos(q3)/lma)] A4=[exp(-2*
LinearBPM
- 这是一个简单的FFT为无电位1 +1 +1 Ð 薛定谔方程的光束传播方法。如果该软件灵活，允许引入的术语（如果是极少数需要包括色散效应高阶导数）。例如，如果一个人渴望解决的一个方程的形式： （四/ dz的+ Ð ^ 2/dx ^ 2 - 0.25 * Ð ^ 3/dx ^ 3）== 0 Ÿ 它可以解决使用以下代码： Ž = linspace（0,1,512） x = linspace（-5,5,1024） psi0 =进出口
svm4
- -s svm类型：SVM设置类型(默认0) 0 -- C-SVC 1 --v-SVC 2 – 一类SVM 3 -- e -SVR 4 -- v-SVR -t 核函数类型：核函数设置类型(默认2) 0 – 线性：u v 1 – 多项式：(r*u v + coef0)^degree 2 – RBF函数：exp(-r|u-v|^2) 3 –sigmoid：tanh(r*u v + coef0) -d degree
DSP-exp
- 这是中国科学技术大学的dsp实验内容，包括FFT，卷积，滤波器设计等内容，可供学习MATLAB以及深入理解dsp原理之用-This is dsp experiment of USTC, including FFT, convolution, filter design, etc., for learning MATLAB and in-depth understanding of the principle of dsp.
fit_ML_laplace
- fit_ML_normal - Maximum Likelihood fit of the laplace distribution of i.i.d. samples!. Given the samples of a laplace distribution, the PDF parameter is found fits data to the probability of the form: p(x) = 1/(2*b)*exp(-abs(x-u)/b)
fit_ML_log_normal
- fit_ML_normal - Maximum Likelihood fit of the laplace distribution of i.i.d. samples!. Given the samples of a laplace distribution, the PDF parameter is found fits data to the probability of the form: p(x) = 1/(2*b)*exp(-abs(x-u)/b)
fit_ML_maxwell
- fit_ML_normal - Maximum Likelihood fit of the log-normal distribution of i.i.d. samples!. Given the samples of a log-normal distribution, the PDF parameter is found fits data to the probability of the form: p(x) = sqrt(1/(2*pi))/(s*x)*
fit_ML_normal
- fit_ML_normal - Maximum Likelihood fit of the normal distribution of i.i.d. samples!. Given the samples of a normal distribution, the PDF parameter is found fits data to the probability of the form: p(r) = sqrt(1/2/pi/sig^2)*exp(-((r-u
fit_ML_rayleigh
- fit_ML_rayleigh - Maximum Likelihood fit of the rayleigh distribution of i.i.d. samples!. Given the samples of a rayleigh distribution, the PDF parameter is found fits data to the probability of the form: p(r)=r*exp(-r^2/(2*s))/s wit
M100295_assign2
- Display the 3-d plot of 2-d functions using perspective projections: cos(ux+vy), sin(ux+vy), sinc(x,y), exp(-(ux+vy)), exp(-|ux+vy|), exp(-|ux+0y|), for all x,y and different values of u & v -Display the 3-d plot of 2-d functions using perspecti
Estimating19609112312005
- Simple exercise that calculate the Taylor expansion of the exponential function. Input variables: degree N vector of evaluation points, x At each step plots the Taylor polynomial and compare with the real function function y=
misc2
- Simple exercise that calculate the Taylor expansion of the exponential function. Input variables: degree N vector of evaluation points, x At each step plots the Taylor polynomial and compare with the real function function y=
exp_micro_s
- 自己在QuartusII9.1及Modelsim新版本中完成的microsequencer实例的工程文件。 1.echo uart,接收rx_data,再回复！ 2.运行时请注意完整路径： D:\EXP\EXP_SOPCbuilder\exp_micro_s 3.UART数据输入问题？ 3.1 MODELSIM中w完信号后，run/restart一次。 3.2 设置clock=20ns。 3.3 命令行中输入uart_drive调出uart_
ASA
- Adaptive Simulated Annealing (ASA) is a C-language code developed to statistically find the best global fit of a nonlinear constrained non-convex cost-function over a D-dimensional space. This algorithm permits an annealing schedule for "temper
source
- function S = steeringv(M,x) define steering vector free space wavelength of 15cm at resonant freq of 2GHz lamda = 0.15 d = lamda/2 inter-element spacing K = 1:M x is DOA of the received signal S = exp((-2*pi*j*(K-1)*d*sin(x))/lamda
Exp-10-D-and-JK-FF
- D & JK FLIP FLOP USING MATLAB SOFTWARE