matlab自动控制入门到精通

半导体激光器的数学计算 对速率方程 可能对你计算有点帮助

说明：  一种信号处理的算法的源代码，自己编的很好用(A signal of a method)

medical imahe compression by wavelet...

Nonlinear Homework Problem - Shahrood university- session 22

提出一种新的显着性检测方法，通过将区域级显着性估计和像素级显着性预测与CNN（表示为CRPSD）相结合。对于像素级显着性预测，通过修改VGGNet体系结构来执行完全卷积神经网络（称为像素级CNN）以执行多尺度特征学习，基于该学习进行图像到图像预测以完成像素级显着性检测。对于区域级显着性估计，首先设计基于自适应超像素的区域生成技术以将图像分割成区域，基于该区域通过使用CNN模型（称为区域级CNN）来估计区域级显着性。通过使用另一CNN（称为融合CNN）融合像素级和区域级显着性以形成nal显着图，并且联合学习像素级CNN和融合CNN。对四个公共基准数据集的大量定量和定性实验表明，所提出的方法大大优于最先进的显着性检测方法。(A new saliency detection method by significant regional level estimates and forecast significant pixel level and CNN (expressed as CRPSD) combined. For pixel-level significant prediction to perform a full convolution neural network by modifying VGGNet architecture (called pixel-level CNN) learning to perform multi-scale features, image to image prediction to complete the pixel level detection based on the significant learning . For regional levels significantly estimate, the first generation technology to design image is divided into regions based on adaptive super-pixel area, based on the model of the region through the use of CNN (CNN called regional level) to estimate regional levels significantly. By using another CNN (CNN called fusion) Fusion pixel level and regional level to form nal significant saliency map, and the Joint Learning pixel level fusion CNN and CNN. Four common reference data set of a large number of quantitative and qualitative experiments show that the proposed m)

采用的是脉冲对消法，是路径规划的实用方法，MIMO OFDM matlab仿真,包括数据分析、绘图等等,基于互功率谱的时延估计，分析了该信号的时域、频域、倒谱，循环谱等。

基于kaiser窗的双谱线插值FFT谐波分析，包括调制，解调，信噪比计算，使用混沌与分形分析的例程，LDPC码的完整的编译码，多姿态，多角度，有不同光照,调试通过可以使用。

对图形进行边缘检测并输出边缘点和该点所在处的灰度变化率。(edge detection and output the edge point and its corresponding gradient.)

基于电网电压定向的三电平并网逆变器的研究(And the three-level inverter grid voltage oriented network based on)

设定码元速率、载波频率、采样速率、码元个数等，先仿真bpsk信号，然后对其求循环谱。采用频域平滑的方法。(Set the symbol rate, carrier frequency, sampling rate, number of symbols and so on, first simulate the BPSK signal, and then calculate the cyclic spectrum. The frequency domain smoothing method is adopted.)