bpsk_ofdm_CodeLDPC_EN

MATLAB程序目标分割与跟踪的程序MATLAB program object segmentation and tracking procedures(MATLAB program object segmentation and tracking procedures MATLAB program object segmentation and tracking procedures)

Import a TDMS file as a matlab object (ob). This is based on the work by Brad Humphreys of ZIN Technologies (he supported v1 of TDMS). I have not tested against v1 but I believe it still supports it.

本函数计算hankel函数一致展开中的变量(This function calculation hankel function unanimously expand the variable)

introduction to water level control system

司守奎 数学建模算法与应用 CUMCM Reference Book(CUMCM Reference Book)

clear all clc t=0:1/1000:10-1/1000 s=sin(2*pi*t) snr=20 s_power=var(s) varience of s linear_snr=10^(snr/10) factor=sqrt(s_power/linear_snr) noise=randn(1,length(s))*factor x=s+noise Ó É SNR¼ Æ Ë ã Ë æ » úÔ ë É ù x1=noise Ô ë É ùÔ ´ Ê ä È ë x2=noise w1=0 È ¨Ï µ Ê ý ³ õ Ö µ w2=0 e=zeros(1,length(x)) y=0 u=0.05 for i=1:10000 LMSË ã ·¨ y(i)=w1*x1(i)+w2*x2(i) e(i)=x(i)-y(i) w1=w1+u*e(i)*x1(i) w2=w2+u*e(i)*x2(i) end figure(1) subplot(4,1,1)

说明 cloudPlot将有助于形象化的一个二维数据集的分布。这是特别有用当在非常大的数据集凡redular阴谋（的x，y, . )只是填充纯色的情节，因为测量点重叠看着对方。 cloudPlot使用内置的例程在MATLAB中轴线设置限制，并适当格点的数据。 MATLAB的释放MATLAB的7.7（R2008b） (Description cloudPlot will help visualize the distribution of a 2-dimensional dataset. It is especially helpful when looking at extremely large datasets where a redular plot(x,y, . ) will just fill the plot with a solid color because the measurement points overlap each other. cloudPlot uses the built-in matlab routines to set the axis limits and grid points appropriate to the data. MATLAB release MATLAB 7.7 (R2008b))

心电信号数据 去噪滤波 IIR FIR 小波去噪等(ECG digital filter IIR,FIR )

EFFICIENT RANDOM VARIATES GENERATOR (from over 50 distributions):Alpha, Anglit, Antilognormal, Arcsin, Bernoulli, Bessel, Beta, Binomial, Bradford, Burr, Cauchy, Chi, Chi-Square (Non-Central), Chi-Square (Central), Cobb-Douglas, Cosine, Double-Exponential, Erlang, Exponential, Extreme-Value, F (Central), F (Non-Central), Fisher-Tippett, Fisk, Frechet, Furry, Gamma, Generalized Inverse Gaussian, Generalized Hyperbolic, Geometric, Gompertz, Gumbel, Half-Cosine, Hyperbolic Secant, Hypergeometric, Inverse Gaussian, Laplace, Logistic, Lognormal, Lomax, Lorentz, Maxwell, Nakagami, Negative Binomial, Normal, Normal-Inverse-Gaussian (NIG), Pareto, Pareto2, Pascal, Planck, Poisson, Quadratic, Rademacher, Rayleigh, Rice, Semicircle, Skellam, Student s-t, Triangular, Truncated Normal, Tukey-Lambda, U-shape, Uniform (continuous), Von Mises, Wald, Weibull, Wigner Semicircle, Yule, Zeta,(EFFICIENT RANDOM VARIATES GENERATOR (from over 50 distributions): Alpha, Anglit, Antilognormal, Arcsin, Bernoulli, Bessel, Beta, Binomial, Bradford, Burr, Cauchy, Chi, Chi-Square (Non-Central), Chi-Square (Central), Cobb-Douglas, Cosine, Double-Exponential, Erlang, Exponential, Extreme-Value, F (Central), F (Non-Central), Fisher-Tippett, Fisk, Frechet, Furry, Gamma, Generalized Inverse Gaussian, Generalized Hyperbolic, Geometric, Gompertz, Gumbel, Half-Cosine, Hyperbolic Secant, Hypergeometric, Inverse Gaussian, Laplace, Logistic, Lognormal, Lomax, Lorentz, Maxwell, Nakagami, Negative Binomial, Normal, Normal-Inverse-Gaussian (NIG), Pareto, Pareto2, Pascal, Planck, Poisson, Quadratic, Rademacher, Rayleigh, Rice, Semicircle, Skellam, Student s-t, Triangular, Truncated Normal, Tukey-Lambda, U-shape, Uniform (continuous), Von Mises, Wald, Weibull, Wigner Sem)

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