cp_als

本程序是用于信号相关分析的实验程序， 主要功能是计算和比较几种信号的相关函数。(Auto Correlation matlab program)

雷达ofdm信号 采用多脉冲发射 利用通信原理中ofdm多载频技术 绝对好用 毕设代码(radar ofdm signal)

根据伪随机序列理论，由混合同余法产生均匀分布的随机数，进而根据中心极限定理来产生高斯噪声。 分析所产生的均匀分布和高斯分布随机信号的均值、方差、自相关等数字特征，估计其概率密度函数并进行分析，估计其功率谱密度并进行分析。说明该高斯噪声是否符合白噪声特性。 对该高斯噪声进行FIR低通滤波，估计输出低通型限带白噪声的功率谱、相关时间等，并结合白噪声通过线性系统相关理论来进行分析。 (According to the theory of pseudo-random sequence, a uniformly distributed random numbers by mixed congruential method to generate Gaussian noise, and then according to the central limit theorem. Produce a uniform distribution of the analysis and the mean of the Gaussian distribution random signals, variance, since the digital characteristics of the correlation, the probability density function is estimated and analyzed, it is estimated that its power spectral density, and analyzed. The Gaussian noise is in line with the characteristics of white noise. FIR low pass filter of the Gaussian noise, the estimated output of low-pass type band-limited white noise power spectrum, time, etc., combined with the white noise to be analyzed by linear system theory.)

该程序用以对m序列码的调制在负dB情况下解调的仿真，是对基带信号的调制(procedures for the right sequence code m in the negative dB modulation of the demodulation simulation of the base band signal modulation)

粒子群算法的Matlab程序实现。不仅提供了源程序，还附带有详细的例子。对于初学者有极大的帮助。(PSO algorithm Matlab programming. Not only provides a source, also comes with detailed examples. There are a great help for beginners.)

By using these matlab codes one can generate any noise with mean X and variance Y . Useful for analysis of signals in noisy environment

以前西电研究生DSP大作业代码，都是C语言和Matlab完整版，可以供大家编程参考 (Former Western Electric graduate DSP great job code, C language and Matlab full version, can be programmed for your reference)

说明：  一个简单的matlab程序，用于滤波，不需要太在意(a simple matlab filter program)

说明：  用PSO求解函数的最大值，有图形界面，适合初学者学习。(a function to find the Max.Value using PSOA, good structure and nice interface.)

模拟带噪声的匀加速直线运动，数据平滑，多个smooth函数的应用，简单易懂(Simulation with the noise of the constant acceleration of linear motion, data smoothing, multiple smooth function of the application, easy to understand)