writting-fast-matlab-code

在自动控制系统的过程中，白噪声的产生方法，MIT 稳定方程 持续时间 稳定时间(The automatic control system of the process, the white noise generation method, MIT stabilization stabilization time duration equation)

对原始信号进行四相相移键控调制，然后加入高斯白噪声，对加噪信号进行解调，对比解调信号与原始信号，计算误码率(The original signal quadrature phase shift keying modulation, and then adding Gaussian white noise, plus noise signal is demodulated, comparing the demodulated signal with the original signal, bit error rate calculation)

包括牛顿法，拉格朗日法，ＬＵ分解法，１００*１００阶稀疏矩阵方程组的解法等(Including the Newton method, Lagrangian method, LU decomposition method, 100* 100 band sparse matrix equations of the solution, etc.)

说明：  描述分形编码和解码原理的非常好的一份电子文档，对实验结果也进行了详细的分析(Describe the principles of fractal coding and decoding an electronic document very well the experimental results carried out a detailed analysis of)

说明：  Цифровой спектральный анализ и его приложения

该代码用于实现粒子滤波视觉目标跟踪(PF)、卡尔曼粒子滤波视觉目标跟踪(KPF)、无迹粒子滤波视觉目标跟踪(UPF)。它们是本人这两年来编写的核心代码，用于实现鲁棒的视觉目标跟踪，其鲁棒性远远超越MeanShift(均值转移)和Camshift之类。用于实现视觉目标跟踪的KPF和UPF都是本人花费精力完成，大家在网上是找不到相关代码的。这些代码虽然只做了部分代码优化，但其优化版本已经成功应用于我们研究组研发的主动视觉目标跟踪打击平台中。现在把它们奉献给大家！(These codes are used to realize particle filter based visual object tracking (PF), kalman particle filter based visual object tracking, unscented particle filter based visual object tracking. Their robustness is far beyond the classical visual object tracking algorithms such as Mean-Shift (MeanShift) and CamShift。The codes of KPF and UPF for visual object tracking cost a great of my energy, and you can not find any relating algorithm codes on internet! Our research group have optimized these codes and applied them to develop a platform for active visual object tracking. Now, I dedicate them to you and wish you love them! )

用MATLAB程序语言实现最优控制的遗传算法( Genetic algorithm)

很有用的源代码，很实用，效果相当好，很值得收藏(Useful source code, very practical, results have been very good, very worthy collection)

通过M atlab 模拟了随机产生的一定概率分布的信号序列, 叠加高斯噪声后利用最大后验概率(MAP)检 测到的误码率, 做出BER~ SNR曲线, 并与理论计算得到的曲线进行比较, 两者吻合.(M atlab simulated by a certain probability distribution of random signal sequence, use of superposition of Gaussian noise is the maximum a posteriori (MAP) detection to the error rate, making BER ~ SNR curves obtained with the theoretical curve of the combined fit.)

实现白噪声、正弦信号和带有白噪声的正弦信号的自相关函数的分析。(Achieve white noise, white noise with a sinusoidal signal and a sinusoidal signal of the autocorrelation function.)