digital_communication

以一个简单的例子对于极值求解的应用进行了分析和介绍(With a simple example of solving for the application of extreme value analysis and presentation of)

籽子群优化算法优化BP神经网络，使用优化后的神经网络对图像进行分割。包括：籽子群优化算法，籽子的编码，最优权值和阈值的后成，基于籽子群优化算法的神经网络的培训，图像的分割。(The BP neural network optimized by Particle Swarm Optimization　algorithm for image segmentation)

这是一段自己编写的基于高斯模型的matlab人脸识别代码(This is a piece I have written matlab face recognition code based on the Gaussian model)

动目标检测（MTD）领域的仿真，画出了加汉明窗之后的频率响应曲线，经调试，可以运行(Moving target detection (MTD) in the field of simulation, draw the frequency response curve after Hamming window, debugging, you can run)

电压型pwm四象限整流器滞环控制实现的matlab 仿真，希望能对大家有所帮助(The four quadrant rectifier hysteresis control strategy implementation)

总结了五中时频分析方法（STFT,Gabor,WVD,PWVD,SPWVD）,并对个别方法进行了对比。每条程序都有详细的说明(Fifth summarized time-frequency analysis method (STFT, Gabor, WVD, PWVD, SPWVD), and the individual methods were compared. Each program has a detailed description)

MUSIC算法[1]是一种基于矩阵特征空间分解的方法。从几何角度讲，信号处理的观测空间可以分解为信号子空间和噪声子空间，显然这两个空间是正交的。信号子空间由阵列接收到的数据协方差矩阵中与信号对应的特征向量组成，噪声子空间则由协方差矩阵中所有最小特征值（噪声方差）对应的特征向量组成。(MUSIC algorithm [1] is a feature space based on matrix decomposition method. From the geometric point of view, the signal processing can be decomposed observation space the signal subspace and the noise subspace, it is clear that the two spaces are orthogonal. Signal Subspace data received by the array covariance matrix and eigenvectors corresponding to the signal component, the noise subspace from the covariance matrix of all the smallest eigenvalue (noise variance) eigenvector components.)

Duffing系统的时域谱图和相空间轨迹绘制，能够帮助初学者很好的理解典型非线性特征(duffing equation Phase plane trajectory)

DSP课程设计_基于MATLAB的FFT算法实现_09通信本2班(DSP course design of _ the FFT algorithm based on MATLAB _09 communication this class 2)

可以实现ofdm的LS信道估计，并与未采用估计时进行比较(The LS can ofdm channel estimation, and with no comparison with estimates)