Matlab-Newton

包含6个*.m文件，分别是adline网络，bp网络，hopfiled网络，字符识别，学习速度自适应，和增强型lms算法的六个仿真算法程序，真是我的珍藏，这次全抖出来了。(contains 6 m*. documents were adline network bp network hopfiled network, character recognition, adaptive learning speed, lms and enhanced algorithm simulation algorithm six procedures, I really treasure this all shake out.)

标准AM振幅调制方式，ma=1.1时的标准AM振幅调制(Standard AM amplitude modulation, ma = 1.1 when the standard AM amplitude modulation)

一个关于图像边缘检测的实用程序-A practical program for image edge check(One on edge detection utility-A practical program for image edge check)

这是“受控自回滑动平均模型”CARMA非线性系统的随机梯度辨识算法，用于参数估计以及模型建模。(This is a " controlled slide back the average model" CARMA nonlinear system stochastic gradient identification algorithm for parameter estimation and modeling.)

leach协议基于matlab代码，可以试试(based on Matlab)

Signal And Sytem Lab_8

Antenna and EM Modeling with MATLAB

mRMR(最小冗余最大相关)的比较好的文档，可参考一下(mRMR (minimum redundancy maximum correlation) of good documentation, reference)

本算法是用于求解四阶累积量的，主要应用在DOA估计。(This algorithm is used to DOA estimation，and it can solve 4th-roder-cumulant )

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)