MATLABkp

说明：  关于功率放大器非线性建模和线性化的两篇论文资料，详细介绍了所采用的模型和相关算法，很有参考价值。(Those papers are related with pa modeling and linearization, which introduce the pa models and algorithms for those models.)

input dlg with more columns

在一个程序中通过修改参数实现三种调制方式，分别是AM、DSB和FM。 注释详细，适合初学者参考。(It s an analog modulation program by change a parameter.The three modulation types are AM, DSB, and FM. The program is easy to read and suitable for beginners.)

comparisions of texture and colour features for image retrival

说明：  应用电导增量法，实现光伏电池最大功率跟踪。(Achieve maximum power tracking of photovoltaic cells)

说明：  本教程提供了使用MATLAB的实践性指导，它基于MATLAB6.0版，内容由浅入深，特别是本书对每一条命令的使用格式都作了详细而又简单明了的说明，并配备了例题加以说明其用法，因此，对于初学者自学是很有帮助(The Guide provides practical guidance to the use of MATLAB, which is based on MATLAB6.0 edition, the content of easy-to-digest, especially the book on the use of each command formats are explained in detail and simple description and sample questions to be equipped with its usage, therefore, self-study is very helpful for beginners)

风速线性滤波器，可对风洞试验及风速实测资料做简单滤波。(Wind speed linear filter can be measured wind speed of wind tunnel tests and information to do simple filtering. )

一维无网格模型,通过这个文件，大家可以学习到无网格法的基本运算方法，是想要学习无网格法的入门之选(it is a file about messless)

采用LSE算法的OFDM系统信道估计表现 (LSE algorithm for OFDM systems with channel estimation performance)

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)