emp

Simple VaR Calculator provides: - Evaluation of return distribution of single asset or portfolio of assets - Volatility forecasts using moving average and exponential algorithm - Value at Risk of single asset or portfolio measurement using parametric and historical simulation. - Historical data can be obtained from simple text file or MS Excel using Matlab Excel Links. (Simple VaR Calculator provides:- Evaluation of return distribution of single asset or portfolio of assets- Volatility forecasts using moving average and exponential algorithm- Value at Risk of single asset or portfolio measurement using parametric and historical simulation .- Historical data can be obtained from simple text file or MS Excel using Matlab Excel Links.)

matlab电路仿真笔记，关于matlab/simulink用于电路仿真的技巧和方法(matlab circuit simulation notes on matlab/simulink for circuit simulation techniques and methods)

system of pv control for basic with error

【matlab编程代做】matlab圣诞树图 可以作为参考使用学习([Do] matlab matlab program generation tree diagram can be used as a reference study)

小波去噪matlab仿真算法，用于ECG心电信号去噪(wavelet filter Matlab)

实现了跟踪算法里的UKF滤波算法，统计了该滤波算法性能 (UKF in the tracking algorithm, statistical filtering algorithm 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)

apply dwt2 on image that related with signal processing

grid Connected invter

i have written the code for linear classifier for n classes.