7.1

说明：  运用多松弛时间，相对于单松弛，具有更好的稳定性，且数值结果更精确(Compared with single relaxation, multi-relaxation time is more stable and the numerical results are more accurate.)

利用预测的方法实现图像的压缩，可以应用于光谱图像谱间去相关(The use of projected images of the compression method can be applied to spectral-spectral images to the relevant)

计算全通滤波器的源程序,根据信道群延迟,计算滤波器系数,用以校正信号相位变化(calculation of the all-pass filter source files, according to the channel group delay, filter coefficients calculated, for the correction signal phase changes)

Color To Gray And back Matlab Code

该程序使用小波包变换分析信号的特征向量和各频率成分的功率谱.(The program uses the wavelet packet analysis of the signal eigenvectors and the frequency components of the power spectrum.)

关于matlab仿真中使用scope工具时的方法技巧，结合实例，简单明了(About the the scope tool matlab simulation method skills, with examples, simple)

this are the basis for the ofdm paper

微电网遗传算法优化，33节点的配电网网络重构，适合初学者学习(Microgrid genetic algorithm optimization, 33 node distribution network reconfiguration, suitable for beginners to learn.)

信号测量时，传感器优化布置的条件数方法。提供自由度信息，输出不同数量传感器的最优布置方案。(signal measurement, the sensor layout optimization of several methods. Provide freedom of information, the number of different sensor output optimal layout of the program.)

比较两个netcdf文件 1。通过添加内部ind2sub1函数remove函数依赖第三方 2。格式化文本(Description NCCMP compares two netcdf files and prints the differences. This function is useful for testing mathematical forecasting or prediction models. USAGE: NCCMP(ncfile1,ncfile2) NCCMP(ncfile1,ncfile2,tolerance,forceCompare) INPUT: ncfile1- name of the NetCDF file to compare ncfile2- name of the NetCDF file to compare tolerance- Compare numeric data using a tolerance threshold forceCompare- if false, exit when first difference is found true: continues to process all variables EXAMPLES: nccmp( old.nc , new.nc ,0.000001) nccmp( old.nc , new.nc ,[],true) FEATURES: 1. Print the differences and their locations 2. Exits when first difference is found or optionally continues to process all variables 3. User defined tolerance threshold to compare the variables TO DO: 1. Specific variable inclusion or exclusion 2. Specific attribute inclusion or exclusion 3. Option to ignore the history attribute 4. Ignore difference between v)