程序

一个关于OMPSK自相关函数的仿真 希望对大家有用(An autocorrelation function on the OFDM simulation of hope for all of us)

BOC(1,1)的编码，BOC(1,1)的功率谱密度，可以完美运行，对做BOC编码的人很有用途(BOC (1,1) code, BOC (1,1) power spectral density, can run perfectly on the very people who make use of BOC coding)

最原始的CV模型的matlab程序，可以很好的运行(initial CV model)

在一个移动通信系统中，发射信号是一个未调制的音频x(t)=cos(2πft)，其中f=f0+fi。设标称载波为f0=1GHz，并设fi =512Hz。假定移动用户在一个繁忙的高速公路上距离基站l公里处的地方，从开始从每小时60公里的速度开始，其速度（在0.01秒的时间间隔内测量）以1/2的概率随机的增加或减少1/10公里每小时。试仿真移动用户在这2s的时间间隔内所接收到的信号(及其频谱)。接收信号可以表示为： y(t)=a(t)Cos[2π(fo+f1)(t-△t)] 式中 △(t)=d(t)/c 且 a(t)=k/d2(t) 在上面的表达式中d(t)是在t时刻基站与移动用户的距离，c是光速，△(t)是传播延迟，而a(t)是信号在t时刻的衰减，并假设在这2s内a(t)是一个常数。利用复低通等效模型来进行仿真。(In a mobile communication system, the transmitted signal is an unmodulated audio x (t) = cos (2πft), where f = f0+ fi. Let nominal carrier of f0 = 1GHz, and set fi = 512Hz. Assume that mobile users on a busy motorway station l kilometers place, starting the beginning of 60 kilometers per hour, the speed (measured in 0.01 second interval) to increase the probability of a random 1/2 or reducing 1/10 km/h. Simulation test signal which the mobile subscriber in the 2s time intervals of the received (and its spectrum). The received signal can be expressed as: y (t) = a (t) Cos [2π (fo+ f1) (t- △ t)] Where △ (t) = d (t)/c And a (t) = k/d2 (t) In the above expression, d (t) at time t is a base station and a mobile user s distance, c is the speed of light, △ (t) is the propagation delay, and a (t) is the attenuation of the signal at time t, and assuming that 2s within a (t) is a constant. Using complex low-pass equivalent model for emulation.)

图像中值滤波，利用中值滤波和低通滤波进行比较，分析PSNR，得出性能差别(image filtering, using median filter and a low-pass filter, PSNR analysis, the performance differences come)

此程序用提升法实现第二代小波变换 ％％ 我用的是非整数阶小波变换 ％％ 采用时域实现,步骤先列后行 ％％ 正变换：分裂，预测，更新； ％％ 反变换：更新，预测，合并 ％％ 只做一层（可以多层，而且每层的预测和更新方程不同）(the procedure used to upgrade method is the second generation wavelet transform%% I use a non-integer-order wavelet transform%% using time domain achieved, steps out first go backward%% transformation : split and forecast updates; %% inverse transformation : Update, forecasting, %% off with a layer (which can be multi-storey, but the typical forecast and updating different equation))

运用C语言对高斯信道进行仿真，简洁快速的实现(The use of C language Gaussian channel simulation, simple rapid implementation)

energy totale in cognitive radio network

是机器学习的例程，包含收发两个客户端的链路级通信程序,通过matlab代码，LCMV优化设计阵列处理信号，有信道编码，调制，信道估计等，均值便宜跟踪的示例。 ( Machine learning routines, Contains two clients receive link-level communications program, By matlab code, LCMV optimization design array signal processing, Channel coding, modulation, channel estimation, Example tracking mean cheap. )

通过java调用matlab中的函数，包括如何做图，如何调用函数等等(java call matlab )