qpsk_ber_no_noise.m

这是关于混沌理论及应用方面的基础资料,希望对大家有帮助,里面含有几个falsh信道模型(This is on the application of chaos theory and the basis of information you would like to help, which contains several falsh channel model)

矩形块的三角形单元的有限元计算程序，实现了单元网格自动剖分，后处理后自动绘图等(Rectangular block triangular element finite element program)

系统辨识的matlab仿真，该方法的辨识过程使用了粒子群算法，计算迅速准确。(Matlab simulation of system identification, the identification of the method using particle swarm optimization algorithm to calculate quickly and accurately.)

matlab simulink buck电路的 PID 仿真模型 matlab 2010以上可用(matlab simulink DC-DC chopper buck PID model matlab version 2010)

正确率可以达到98％，利用matlab写成的窄带噪声发生，使用高阶累积量对MPSK信号进行调制识别。( Accuracy can reach 98 , Using matlab written narrowband noise occurs, Using high-order cumulants of MPSK signal modulation recognition.)

一维连续功率谱分析 一维序列x(n)的连续功率谱分析，ol(0:m)频率，tl(0:m)周期，sl(0:m)连续功率谱，st95(0:m)红噪音或白噪音谱的95 置信上限，strw(0:m) 红噪音或白噪音的谱密度，其中m=[n/2.]。 (Continuous power spectral analysis of one-dimensional one-dimensional sequence x (n) of continuous power spectrum analysis, ol (0: m) frequency, tl (0: m) cycle, sl (0: m) continuous power spectrum, st95 (0: m ) red noise or white noise spectrum of the 95 confidence limit, strw (0: m) of red noise or white noise spectral density, where m = [n/2.].)

说明：  典型关联分析(Canonical Correlation Analysis，以下简称CCA)是最常用的挖掘数据关联关系的算法之一。(Canonical Association Analysis (CCA) is one of the most commonly used algorithms for mining data association.)

说明：  差分粒子群算法是一种新的模仿鸟类群体行为的智能优化算法，现已成为进化算法的一个新的重要分支。在基本粒子群算法和改进粒子群算法原理的基础上，实现了粒子群算法在函数优化、图像压缩和基因聚类中的应用。(Differential particle swarm optimization (DPSO) is a new intelligent optimization algorithm which imitates the behavior of bird swarm. It has become a new important branch of evolutionary algorithm. Based on the basic particle swarm optimization (PSO) algorithm and the improved principle of PSO, the application of PSO in function optimization, image compression and gene clustering is realized.)

Matlab-频谱分析实例，大家有需要的可以下载来看看，谢谢支持(Matlab)

windows 驱动备份, 采用c sharp开发.(windows driver backup, using c sharp development.)