matchfilter_sin_signal

一大学生编写的基于小波理论的图像重构和降噪演示，理论例程适合初学(image identification by wavelete )

说明：  一篇有关人脸识别的文章，是2010年在国外做访问学者时下载的，仅供参考(An article on face recognition, in 2010 when a visiting scholar in foreign downloaded for reference purposes only)

FDD链路的仿真使用的是KA波段，其中在接收端涉及到多种算法（位同步算法，DD算法等）(FDD link simulation using KA band)

功能还算完善，可能最后调试有小的问题，但是功能模块基本实现(just do it)

For speckle reduction .

给出了不相关情形下，对累积概率公式检验的程序。(Irrelevant given circumstances, the right formula for the cumulative probability of testing procedures.)

TVL1重建从混合压缩采样，rice大学泊松分布图像重建与全变分正规化的代码(Note: (1)Fore small-scale data, hybrid sampling consists of Bernoulli random sampling and low-resolution sampling (TVL1_HCS) (1)Fore large-scale data, hybrid sampling consists of Fourier radial sampling and low-frequency sampling (TV_RecPF) Copyright (C) 2010 Xianbiao Shu, Computer Vision and Robotics Lab, University of Illinois at Urbana-Champaign. Acknowledgement: RecPF (Rice University) PDCO (Stanford University) Twister (MIT) Reference: X. Shu, N. Ahuja, Hybrid Compressive Sampling via a New Total Variation TVL1, In Proceedings of ECCV 2010. Usage: >> run_me_first >>[Im_rec, PSNR_est1,PSNR_est2] = TVL1L2_HCS_test( Ball1_32.bmp , 0.35,3) >>[Im_rec, PSNR_est1,PSNR_est2] = TVL1L2_HCS_test( Ball1_32.bmp , 0.35,3) >>[Im_rec, PSNR1, PSNR2, G_error, Ratio] = TV_RecPF_test( Chest.png , 5, 10, 0, 1e-10, 0) )

通过对现在汽车前轮转向机构的分析，设计了其优化算法。(By now the front wheel steering motor vehicle analysis, design of its optimization algorithm.)

灵敏度分析源程序，可用于结构模型修正，但仅运用了自振频率信息，没有运用振型信息(Sensitivity analysis of source code, can be used for structural model updating, but only the use of natural frequency information, there is no information on the use of modal)

本文采用最小二乘支持向量机（LSSVM）模型，根据浙江台州某地区的历史负荷数据和气象数据，分析影响预测的各种因素，总结了负荷变化的规律性，对历史负荷数据中的“异常数据”进行修正，对负荷预测中要考虑的相关因素进行了归一化处理。LSSVM中的两个参数对模型有很大影响，而目前依然是基于经验的办法解决。对此，本文采用粒子群优化算法对模型参数进行寻优，以测试集误差作为判决依据，实现模型参数的优化选择，使得预测精度有所提高。实际算例表明，本文的预测方法收敛性好、有较高的预测精度和较快的训练速度。(this paper adopted particle swarm optimization algorithm to optimized the model parameters, make the test set error as the judgments, realized the optimization of model parameters, maked prediction accuracy improved. Practical examples show that convergence of prediction method was pefect, had a higher prediction accuracy and fast training speed.)