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Ìõ¼þt=[0.0100 0.6800 1.1000 1.6300 2.0700 2.6700 3.0900 3.6400 4.6500 5.1000 5.5800 6.1100 6.6300 7.0600 7.6200 8.6600 9.0400 9.6300]; y=[2.3291 3.8513 4.5009 6.7492 9.1121 9.6917 11.1693 10.9145 16.4428 18.2962 21.6399 25.7861 26.3428 26.5058 27.6395 35.0276 35.5562 36.1039]; ·½³ÌDy=-k*y*z+0.095*b*z , Dz=-b*z-0.222*z, y(0)=0, z(0)=5300 zÖ»ÖªµÀ³õʼֵ£¬¹ý³ÌÖµÎÞ·¨²â¶¨£¬ÒªÇóͨ¹ý·½³ÌÄâºÏµÃ³ökºÍbµÄÖµ ͨ¹ý[y,z]=dsolve('Dy=-k*y*z+0.995*b*z','Dz=-b*z-0.222*z','y(0)=0,z(0)=5300','t')µÃ³öyµÄ±í´ïʽ£¬ y = (199/200*b/k*exp(-2650000*k/(500*b+111)*exp(-1/500*(500*b+111)*t))-199/200*b/exp(5300*k/(500*b+111))^500/k)*exp(2650000*k/(500*b+111)*exp(-1/500*(500*b+111)*t)) z =5300*exp((-b-111/500)*t) È»ºó myfunc=inline('(199./200.*beta(2)./beta(1).*exp(-2650000.*beta(1)./(500.*beta(2)+111).*exp(-1./500*(500.*beta(2)+111).*t))-199./200.*beta(2)./exp(5300.*beta(1)/(500.*beta(2)+111)).^500/beta(1)).*exp(2650000.*beta(1)/(500.*beta(2)+111).*exp(-1./500*(500.*beta(2)+111).*t))','beta','t') ²ÉÓÃnlinfitÄâºÏ beta=nlinfit(t,y,myfunc,[0.1 0.1]) ³öÏÖÒÔÏ´íÎó ??? Error using ==> nlinfit>checkFunVals at 357 MODELFUN has returned Inf or NaN values. Error in ==> nlinfit>LMfit at 304 if funValCheck && ~isfinite(sse), checkFunVals(r); end Error in ==> nlinfit at 167 [beta,J,lsiter,cause] = LMfit(X,y, model,beta,options,verbose,maxiter); Çë¸÷λ°ïæ½â¾öÒ»ÏÂÕâ¸öÎÊÌ⣬·Ç³£¼±ÇÐÐèÒª |
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wuguocheng(½ð±Ò+1,VIP+0): ллÌÖÂÛ 10-24 08:06
wuguocheng(½ð±Ò+1,VIP+0): ллÌÖÂÛ 10-24 08:06
| did you try to change your initial guess of beta. looks like there are NAN during function evaluation |
2Â¥2009-10-24 05:56:21














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