function [U,center,result,w,obj_fcn]= fenlei(data) [data_n,in_n] = size(data) m= 2 ％ Exponent for U max_iter = 100 ％ Max. iteration min_impro =1e-5 ％ Min. improvement c=3 [center, U, obj_fcn] = fcm(data, c) for i=1:max_iter if F(U)>0.98 break else w_new=eye(in_n,in_n) center1=sum(center)/c a=center1(1)./center1 deta=center-center1(ones(c,1),:) w=sqrt(sum(deta.^2)).*a for j=1:in_n w_new(j,j)=w(j) end data1=data*w_new [center, U, obj_fcn] = fcm(data1, c) center=center./w(ones(c,1),:) obj_fcn=obj_fcn/sum(w.^2) end end display(i) result=zeros(1,data_n) U_=max(U) for i=1:data_n for j=1:c if U(j,i)==U_(i) result(i)=j continue end end end
标签： data function Exponent obj_fcn
上传时间： 2013-12-18
上传用户：ynzfm
function [U,V,num_it]=fcm(U0,X) ％ MATLAB (Version 4.1) Source Code (Routine fcm was written by Richard J. ％ Hathaway on June 21, 1994.) The fuzzification constant ％ m = 2, and the stopping criterion for successive partitions is epsilon =??????. ％*******Modified 9/15/04 to have epsilon = 0.00001 and fix univariate bug******** ％ Purpose:The function fcm attempts to find a useful clustering of the ％ objects represented by the object data in X using the initial partition in U0.
标签： fcm function Version Routine
上传时间： 2014-11-30
上传用户：二驱蚊器
function varargout = lcmgui(varargin) ％ LCMGUI M-file for lcmgui.fig ％ LCMGUI, by itself, creates a new LCMGUI or raises the existing
标签： LCMGUI lcmgui varargout function
上传时间： 2016-12-20
上传用户：cxl274287265
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. ％
标签： generalization calculates prediction function
上传时间： 2014-12-03
上传用户：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. ％
标签： generalization calculates prediction function
上传时间： 2016-12-27
上传用户：脚趾头
This function applies the Optimal Brain Surgeon (OBS) strategy for ％ pruning neural network models of dynamic systems. That is networks ％ trained by NNARX, NNOE, NNARMAX1, NNARMAX2, or their recursive ％ counterparts.
标签： function strategy Optimal Surgeon
上传时间： 2013-12-19
上传用户：ma1301115706
Please carefully read the many features of your package and then write the specific function (at least 20 words). As far as possible not to let the station master of the time spent in the
标签： carefully the features function
上传时间： 2013-12-16
上传用户：ouyangtongze
This function checks the mailbox to see if a message is available. Unlike OSMboxPend(), OSMboxAccept() does not suspend the calling task if a message is not available.
标签： OSMboxAccep OSMboxPend available function
上传时间： 2014-12-04
上传用户：hphh
For Batch Estimation Method, the function and code supplyment.
标签： Estimation supplyment function Method
上传时间： 2017-01-01
上传用户：gououo
Linux C function() 参考手册 各位Linux爱好者： 你好！本人有幸在坊间得到一名为“Linux C 函数参考”的文本文件，并在此基础重新排版并制成html文件以方便广大爱好者阅读，我感到无比的荣幸。在此多谢各位的鼎力支持，以及日益完善此文件，希望有朝一日能成为Linux编程爱好者必备的参考文件。在此再次多谢编写“Linux C 函数参考”的朋友。
上传时间： 2017-01-07
上传用户：zaizaibang
