function [beta,alfa] = AIDyadDown(afine,D,F,EF) ％ AIDyadDown -- average-Interpolating DownSampling Operator
標簽： AIDyadDown average-Interpolating DownSampling function
上傳時間： 2014-01-14
上傳用戶：redmoons
This program will ask how many numbers you want to find the average of, then it will allow you to enter your numbers(yes they can even be decimals) then it will calculate the mean, median, mode and range of what you enter.
上傳時間： 2015-03-23
上傳用戶：skhlm
An AutoRegressive Moving Average Spectral Analysis toolbox for use with Matlab.
標簽： AutoRegressive Analysis Spectral Average
上傳時間： 2014-01-17
上傳用戶：yepeng139
Nand Flash Translation Layer 用于nandflash的操作。 bad block memory map garbage collection average erase
標簽： Translation collection nandflash average
上傳時間： 2014-07-02
上傳用戶：lingzhichao
krigging model for interpolating data
標簽： interpolating krigging model data
上傳時間： 2013-12-25
上傳用戶：hakim
using judgement on average power overflow or too small to implement the protection on amplifier
標簽： protection judgement amplifier implement
上傳時間： 2013-12-27
上傳用戶：頂?shù)弥?/p>
matlab ofdm signal simulation. PAPR(peak to average power ratio) modeling.
標簽： simulation modeling average matlab
上傳時間： 2013-11-27
上傳用戶：ouyangtongze
This an interpolating by 2 half-band filter with 79 taps (40 none-zero coefficients).
標簽： interpolating coefficients half-band none-zero
上傳時間： 2016-10-07
上傳用戶：Andy123456
This function calculates Akaike s final prediction error ％ estimate of the average generalization error. ％ ％ [FPE,deff,varest,H] = fpe(NetDef,W1,W2,PHI,Y,trparms) produces the ％ final prediction error estimate (fpe), the effective number of ％ weights in the network if the network has been trained with ％ weight decay, an estimate of the noise variance, and the Gauss-Newton ％ Hessian. ％
標簽： generalization calculates prediction function
上傳時間： 2014-12-03
上傳用戶：maizezhen
This function calculates Akaike s final prediction error ％ estimate of the average generalization error for network ％ models generated by NNARX, NNOE, NNARMAX1+2, or their recursive ％ counterparts. ％ ％ [FPE,deff,varest,H] = nnfpe(method,NetDef,W1,W2,U,Y,NN,trparms,skip,Chat) ％ produces the final prediction error estimate (fpe), the effective number ％ of weights in the network if it has been trained with weight decay, ％ an estimate of the noise variance, and the Gauss-Newton Hessian. ％
標簽： generalization calculates prediction function
上傳時間： 2016-12-27
上傳用戶：腳趾頭
