reconstr

frequency synchronization for ofdm

用实验方法测试RLC串联谐振电路的幅频特性曲线。当正弦交流信号的频率f改变时，电路的感抗、容抗随之而变.取电路电压U0作为响应，当输入电压Ui幅值维持不变时，在不同信号频率的激励下，测出U0之值，用LabVIEW程序完成频谱分析和滤波，变换等信号处理，即可测出RLC串联电路的谐振频率，(Amplitude-frequency characteristics experimentally tested RLC series resonant circuit curve. When changing the frequency f of the sinusoidal AC signal, the circuit inductance, capacitance change with Take circuit voltage U0 as a response when the amplitude of the input voltage Ui unchanged, signals at different excitation frequencies, the measured value U0, the process is complete spectrum analysis using LabVIEW and filtering, transform signal processing, can be measured RLC series circuit resonant frequency,)

宽带信号源测向的一种新方法,TOPS方法的源程序(A new DOA estimation method,TOPS method , for broadband sources)

中心显示格式和修正中心显示格式求解poisson方程，矩形区域，狄利克雷边界情况！(Center display format and the correction center display format for solving poisson equations, rectangular area, Dirichlet boundary conditions!)

说明：  自己做的几个涉及到测量的子程序，有坐标反算、排序、角度转换、时间处理、四舍六入、三维显示等等(Yourself a few involves measurement subroutine, are calculated by coordinates, sorting, Angle conversion, time processing, and six into four, three dimensional display and so on)

该程序为qpsk的完整仿真程序。需要的可以下了看下 可以运行(qpsk the procedure for the complete simulation program. They may need to run the facie)

这些MATLAB函数分别为数字图像处理Matlab版，由冈萨雷斯著作的，补充和扩展MATLAB的图像处理功能和图像处理工具箱提供MathWorks。(These MATLAB functions were created for the book Digital Image Processing Using MATLAB (DIPUM), by R.C. Gonzalez, R.E. Woods, and S.L. Eddins, Prentice Hall, 2004, ISBN 0130085197. The functions supplement and extend the image processing functionality of MATLAB and the Image Processing Toolbox, both offered by The MathWorks.)

数字减影(DSA:Digital Subtract Angiography)是一种传统的血管可视化技术[1]。这一技术用注射造影剂后的活动图像减去注射造影剂前记录的掩模图像来显示不透明的血管。其期望的结果是在减影后的图像上背景结构被完全消除。(estimation based on background)

说明：  主成分分析的matlab源程序，用以标准化数据，精简指标，减少指标之间信息的重叠。(Principal component analysis matlab source for standardized data, streamline indicators, reduce duplication of information between indicators)

基于二阶泛模型的无模型自适应控制及参数整定，充分利用无模型自适应控制边建模边控制的特点，推导基于二阶泛模型的改进无模型自适应控制，应用辨识出的近似模型针对不同目标函数进行优化(Pan model based on second order approximation model of model-free adaptive control and parameter tuning, make full use of model-free adaptive control side edge control modeling features derived model-free adaptive control model based on improved second-order pan, identify the application The objective function to be optimized for different)