Wolfram mathematica Mathematica中的广义特征值

Wolfram mathematica Mathematica中的广义特征值,wolfram-mathematica,eigenvector,Wolfram Mathematica,Eigenvector,我想用Mathematica解决一个广义特征值问题。我想找到矩阵A相对于B的本征值和本征向量。但是当我使用本征系统时,我收到以下错误 A = {{1, 2, 3}, {3, 6, 8}, {5, 9, 2}} B = {{3, 5, 7}, {1, 7, 9}, {4, 6, 2}} Eigensystem[{A, B}] Eigensystem::exnum: Eigensystem has received a matrix with non-numerical or exact ele

我想用Mathematica解决一个广义特征值问题。我想找到矩阵A相对于B的本征值和本征向量。但是当我使用
本征系统
时,我收到以下错误

A = {{1, 2, 3}, {3, 6, 8}, {5, 9, 2}}
B = {{3, 5, 7}, {1, 7, 9}, {4, 6, 2}}
Eigensystem[{A, B}]

Eigensystem::exnum: Eigensystem has received a matrix with non-numerical or exact 
elements. >>

我该怎么办?

好吧,至于你能做什么,你可以在那里抛出一个
N[]

至于你为什么会犯这样的错误,我现在不确定。可能是别人知道的

A={{1,2,3},{3,6,8},{5,9,2}};
B={{3,5,7},{1,7,9},{4,6,2}};
Eigensystem[{N@A,N@B}]

Out[48]= {{1.6359272851306594,0.52597489217711,0.011174745769153706},
 {{0.0936814383974197,0.7825455672726674,-0.6155048523299302},
 {-0.8489102791046691,0.3575364071543101,0.389254486922913},
 {0.8701002165041747,-0.4913210011447429,0.03910610020848224}}}     

好吧,至于你能做什么,你可以在那里抛出一个
N[]

至于你为什么会犯这样的错误,我现在不确定。可能是别人知道的

A={{1,2,3},{3,6,8},{5,9,2}};
B={{3,5,7},{1,7,9},{4,6,2}};
Eigensystem[{N@A,N@B}]

Out[48]= {{1.6359272851306594,0.52597489217711,0.011174745769153706},
 {{0.0936814383974197,0.7825455672726674,-0.6155048523299302},
 {-0.8489102791046691,0.3575364071543101,0.389254486922913},
 {0.8701002165041747,-0.4913210011447429,0.03910610020848224}}}     
直接从复制,使用可逆矩阵,您可以使用它获得精确的结果作为
根对象:

A = {{1, 2, 3}, {3, 6, 8}, {5, 9, 2}};
B = {{3, 5, 7}, {1, 7, 9}, {4, 6, 2}};

Eigensystem[Inverse[B].A] // RootReduce
{{根[-1+92#1-226#1^2+104#1^3&,3], 根[-1+92#1-226#1^2+104#1^3&,2], 根[-1+92#1-226#1^2+104#1^3&,1]}, {{根[-1418-9903#1-3824#1^2+192#1^3&,2], 根[-2817+627#1+2480#1^2+192#1^3&,2],1}, {Root[-1418-9903#1-3824#1^2+192#1^3&,1], 根[-2817+627#1+2480#1^2+192#1^3&,3],1}, {Root[-1418-9903#1-3824#1^2+192#1^3&,3], 根[-2817+627#1+2480#1^2+192#1^3&,1],1}}}}直接从中复制,使用可逆矩阵,您可以使用它获得精确的结果,如
对象:

A = {{1, 2, 3}, {3, 6, 8}, {5, 9, 2}};
B = {{3, 5, 7}, {1, 7, 9}, {4, 6, 2}};

Eigensystem[Inverse[B].A] // RootReduce
{{根[-1+92#1-226#1^2+104#1^3&,3], 根[-1+92#1-226#1^2+104#1^3&,2], 根[-1+92#1-226#1^2+104#1^3&,1]}, {{根[-1418-9903#1-3824#1^2+192#1^3&,2], 根[-2817+627#1+2480#1^2+192#1^3&,2],1}, {Root[-1418-9903#1-3824#1^2+192#1^3&,1], 根[-2817+627#1+2480#1^2+192#1^3&,3],1}, {Root[-1418-9903#1-3824#1^2+192#1^3&,3],
如果你做了改变,如果你做了改变,如果你做了改变,如果你做了改变<代码>特征系统的特征系统[{{a,b},b}{a,b}//{N{a,b}}}如果你做了改变,如果你做了改变<代码>特征系统[{代码>特征系统[{a,b{a,b},b}//,NN,NN
作为答案。如何区分特征向量和特征值?(对不起,我对mathematica很陌生)如果你改变特征系统[{a,b}//N],使矩阵项不是精确的数字,Mma不会抱怨,并给出
{1.63593,0.525975,0.0111747},{0.0936814,0.782546,-0.615505},{-0.84891,0.357536,0.389254},{0.8701,-0.491321,0.0391061}
作为答案。如何区分特征向量和特征值?(对不起,我对mathematica很陌生)